So I start a tlt train command at
2021-07-02 12:20:11,719
at
2021-07-02 12:20:27,750 - loading a model (3 minutes)
2021-07-02 12:23:20,990 - message about dataset (I have 10 images in dataset)
…
I wait here for several minutes
+
10 minutes for 1 epoch
…
Epoch 1/1
2/10 [=====>…] - ETA: 34:42 - loss: 96.4671 /usr/local/lib/python3.6/dist-packages/keras/callbacks.py:122: UserWarning: Method on_batch_end() is slow compared to the batch update (3.052041). Check your callbacks.
% delta_t_median)
10/10 [==============================] - 522s 52s/step - loss: 92.5794
Whole logs
To run with multigpu, please change --gpus based on the number of available GPUs in your machine.
2021-07-02 14:20:11,719 [INFO] root: Registry: ['nvcr.io']
2021-07-02 14:20:11,998 [WARNING] tlt.components.docker_handler.docker_handler:
Docker will run the commands as root. If you would like to retain your
local host permissions, please add the "user":"UID:GID" in the
DockerOptions portion of the ~/.tlt_mounts.json file. You can obtain your
users UID and GID by using the "id -u" and "id -g" commands on the
terminal.
Using TensorFlow backend.
Using TensorFlow backend.
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:117: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
2021-07-02 12:20:17,634 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:117: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:143: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
2021-07-02 12:20:17,634 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/horovod/tensorflow/__init__.py:143: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:52: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
2021-07-02 12:20:17,760 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:52: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.
WARNING:tensorflow:From /opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:55: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
2021-07-02 12:20:17,761 [WARNING] tensorflow: From /opt/tlt/.cache/dazel/_dazel_tlt/2b81a5aac84a1d3b7a324f2a7a6f400b/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:55: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
2021-07-02 12:20:18,079 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:517: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
2021-07-02 12:20:18,080 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4138: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
2021-07-02 12:20:18,097 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1834: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead.
WARNING:tensorflow:From /opt/nvidia/third_party/keras/tensorflow_backend.py:183: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.
2021-07-02 12:20:19,463 [WARNING] tensorflow: From /opt/nvidia/third_party/keras/tensorflow_backend.py:183: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:2018: The name tf.image.resize_nearest_neighbor is deprecated. Please use tf.compat.v1.image.resize_nearest_neighbor instead.
2021-07-02 12:20:19,488 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:2018: The name tf.image.resize_nearest_neighbor is deprecated. Please use tf.compat.v1.image.resize_nearest_neighbor instead.
WARNING:tensorflow:From /opt/nvidia/third_party/keras/tensorflow_backend.py:187: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
2021-07-02 12:20:22,664 [WARNING] tensorflow: From /opt/nvidia/third_party/keras/tensorflow_backend.py:187: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.
2021-07-02 12:20:23,062 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:174: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:199: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.
2021-07-02 12:20:23,063 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:199: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:206: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.
2021-07-02 12:20:24,383 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:206: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/optimizers.py:790: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.
2021-07-02 12:20:26,412 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/optimizers.py:790: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:3295: The name tf.log is deprecated. Please use tf.math.log instead.
2021-07-02 12:20:26,416 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:3295: The name tf.log is deprecated. Please use tf.math.log instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:986: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.
2021-07-02 12:20:27,418 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:986: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:973: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.
2021-07-02 12:20:27,750 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:973: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
Input (InputLayer) (None, 3, 384, 384) 0
__________________________________________________________________________________________________
conv1 (Conv2D) (None, 64, 192, 192) 9408 Input[0][0]
__________________________________________________________________________________________________
bn_conv1 (BatchNormalization) (None, 64, 192, 192) 256 conv1[0][0]
__________________________________________________________________________________________________
activation_2 (Activation) (None, 64, 192, 192) 0 bn_conv1[0][0]
__________________________________________________________________________________________________
block_1a_conv_1 (Conv2D) (None, 64, 96, 96) 4096 activation_2[0][0]
__________________________________________________________________________________________________
block_1a_bn_1 (BatchNormalizati (None, 64, 96, 96) 256 block_1a_conv_1[0][0]
__________________________________________________________________________________________________
block_1a_relu_1 (Activation) (None, 64, 96, 96) 0 block_1a_bn_1[0][0]
__________________________________________________________________________________________________
block_1a_conv_2 (Conv2D) (None, 64, 96, 96) 36864 block_1a_relu_1[0][0]
__________________________________________________________________________________________________
block_1a_bn_2 (BatchNormalizati (None, 64, 96, 96) 256 block_1a_conv_2[0][0]
__________________________________________________________________________________________________
block_1a_relu_2 (Activation) (None, 64, 96, 96) 0 block_1a_bn_2[0][0]
__________________________________________________________________________________________________
block_1a_conv_3 (Conv2D) (None, 256, 96, 96) 16384 block_1a_relu_2[0][0]
__________________________________________________________________________________________________
block_1a_conv_shortcut (Conv2D) (None, 256, 96, 96) 16384 activation_2[0][0]
__________________________________________________________________________________________________
block_1a_bn_3 (BatchNormalizati (None, 256, 96, 96) 1024 block_1a_conv_3[0][0]
__________________________________________________________________________________________________
block_1a_bn_shortcut (BatchNorm (None, 256, 96, 96) 1024 block_1a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_17 (Add) (None, 256, 96, 96) 0 block_1a_bn_3[0][0]
block_1a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_1a_relu (Activation) (None, 256, 96, 96) 0 add_17[0][0]
__________________________________________________________________________________________________
block_1b_conv_1 (Conv2D) (None, 64, 96, 96) 16384 block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_bn_1 (BatchNormalizati (None, 64, 96, 96) 256 block_1b_conv_1[0][0]
__________________________________________________________________________________________________
block_1b_relu_1 (Activation) (None, 64, 96, 96) 0 block_1b_bn_1[0][0]
__________________________________________________________________________________________________
block_1b_conv_2 (Conv2D) (None, 64, 96, 96) 36864 block_1b_relu_1[0][0]
__________________________________________________________________________________________________
block_1b_bn_2 (BatchNormalizati (None, 64, 96, 96) 256 block_1b_conv_2[0][0]
__________________________________________________________________________________________________
block_1b_relu_2 (Activation) (None, 64, 96, 96) 0 block_1b_bn_2[0][0]
__________________________________________________________________________________________________
block_1b_conv_3 (Conv2D) (None, 256, 96, 96) 16384 block_1b_relu_2[0][0]
__________________________________________________________________________________________________
block_1b_conv_shortcut (Conv2D) (None, 256, 96, 96) 65536 block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_bn_3 (BatchNormalizati (None, 256, 96, 96) 1024 block_1b_conv_3[0][0]
__________________________________________________________________________________________________
block_1b_bn_shortcut (BatchNorm (None, 256, 96, 96) 1024 block_1b_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_18 (Add) (None, 256, 96, 96) 0 block_1b_bn_3[0][0]
block_1b_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_1b_relu (Activation) (None, 256, 96, 96) 0 add_18[0][0]
__________________________________________________________________________________________________
block_1c_conv_1 (Conv2D) (None, 64, 96, 96) 16384 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_1c_bn_1 (BatchNormalizati (None, 64, 96, 96) 256 block_1c_conv_1[0][0]
__________________________________________________________________________________________________
block_1c_relu_1 (Activation) (None, 64, 96, 96) 0 block_1c_bn_1[0][0]
__________________________________________________________________________________________________
block_1c_conv_2 (Conv2D) (None, 64, 96, 96) 36864 block_1c_relu_1[0][0]
__________________________________________________________________________________________________
block_1c_bn_2 (BatchNormalizati (None, 64, 96, 96) 256 block_1c_conv_2[0][0]
__________________________________________________________________________________________________
block_1c_relu_2 (Activation) (None, 64, 96, 96) 0 block_1c_bn_2[0][0]
__________________________________________________________________________________________________
block_1c_conv_3 (Conv2D) (None, 256, 96, 96) 16384 block_1c_relu_2[0][0]
__________________________________________________________________________________________________
block_1c_conv_shortcut (Conv2D) (None, 256, 96, 96) 65536 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_1c_bn_3 (BatchNormalizati (None, 256, 96, 96) 1024 block_1c_conv_3[0][0]
__________________________________________________________________________________________________
block_1c_bn_shortcut (BatchNorm (None, 256, 96, 96) 1024 block_1c_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_19 (Add) (None, 256, 96, 96) 0 block_1c_bn_3[0][0]
block_1c_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_1c_relu (Activation) (None, 256, 96, 96) 0 add_19[0][0]
__________________________________________________________________________________________________
block_2a_conv_1 (Conv2D) (None, 128, 48, 48) 32768 block_1c_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_1 (BatchNormalizati (None, 128, 48, 48) 512 block_2a_conv_1[0][0]
__________________________________________________________________________________________________
block_2a_relu_1 (Activation) (None, 128, 48, 48) 0 block_2a_bn_1[0][0]
__________________________________________________________________________________________________
block_2a_conv_2 (Conv2D) (None, 128, 48, 48) 147456 block_2a_relu_1[0][0]
__________________________________________________________________________________________________
block_2a_bn_2 (BatchNormalizati (None, 128, 48, 48) 512 block_2a_conv_2[0][0]
__________________________________________________________________________________________________
block_2a_relu_2 (Activation) (None, 128, 48, 48) 0 block_2a_bn_2[0][0]
__________________________________________________________________________________________________
block_2a_conv_3 (Conv2D) (None, 512, 48, 48) 65536 block_2a_relu_2[0][0]
__________________________________________________________________________________________________
block_2a_conv_shortcut (Conv2D) (None, 512, 48, 48) 131072 block_1c_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_3 (BatchNormalizati (None, 512, 48, 48) 2048 block_2a_conv_3[0][0]
__________________________________________________________________________________________________
block_2a_bn_shortcut (BatchNorm (None, 512, 48, 48) 2048 block_2a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_20 (Add) (None, 512, 48, 48) 0 block_2a_bn_3[0][0]
block_2a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_2a_relu (Activation) (None, 512, 48, 48) 0 add_20[0][0]
__________________________________________________________________________________________________
block_2b_conv_1 (Conv2D) (None, 128, 48, 48) 65536 block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_bn_1 (BatchNormalizati (None, 128, 48, 48) 512 block_2b_conv_1[0][0]
__________________________________________________________________________________________________
block_2b_relu_1 (Activation) (None, 128, 48, 48) 0 block_2b_bn_1[0][0]
__________________________________________________________________________________________________
block_2b_conv_2 (Conv2D) (None, 128, 48, 48) 147456 block_2b_relu_1[0][0]
__________________________________________________________________________________________________
block_2b_bn_2 (BatchNormalizati (None, 128, 48, 48) 512 block_2b_conv_2[0][0]
__________________________________________________________________________________________________
block_2b_relu_2 (Activation) (None, 128, 48, 48) 0 block_2b_bn_2[0][0]
__________________________________________________________________________________________________
block_2b_conv_3 (Conv2D) (None, 512, 48, 48) 65536 block_2b_relu_2[0][0]
__________________________________________________________________________________________________
block_2b_conv_shortcut (Conv2D) (None, 512, 48, 48) 262144 block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_bn_3 (BatchNormalizati (None, 512, 48, 48) 2048 block_2b_conv_3[0][0]
__________________________________________________________________________________________________
block_2b_bn_shortcut (BatchNorm (None, 512, 48, 48) 2048 block_2b_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_21 (Add) (None, 512, 48, 48) 0 block_2b_bn_3[0][0]
block_2b_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_2b_relu (Activation) (None, 512, 48, 48) 0 add_21[0][0]
__________________________________________________________________________________________________
block_2c_conv_1 (Conv2D) (None, 128, 48, 48) 65536 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_2c_bn_1 (BatchNormalizati (None, 128, 48, 48) 512 block_2c_conv_1[0][0]
__________________________________________________________________________________________________
block_2c_relu_1 (Activation) (None, 128, 48, 48) 0 block_2c_bn_1[0][0]
__________________________________________________________________________________________________
block_2c_conv_2 (Conv2D) (None, 128, 48, 48) 147456 block_2c_relu_1[0][0]
__________________________________________________________________________________________________
block_2c_bn_2 (BatchNormalizati (None, 128, 48, 48) 512 block_2c_conv_2[0][0]
__________________________________________________________________________________________________
block_2c_relu_2 (Activation) (None, 128, 48, 48) 0 block_2c_bn_2[0][0]
__________________________________________________________________________________________________
block_2c_conv_3 (Conv2D) (None, 512, 48, 48) 65536 block_2c_relu_2[0][0]
__________________________________________________________________________________________________
block_2c_conv_shortcut (Conv2D) (None, 512, 48, 48) 262144 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_2c_bn_3 (BatchNormalizati (None, 512, 48, 48) 2048 block_2c_conv_3[0][0]
__________________________________________________________________________________________________
block_2c_bn_shortcut (BatchNorm (None, 512, 48, 48) 2048 block_2c_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_22 (Add) (None, 512, 48, 48) 0 block_2c_bn_3[0][0]
block_2c_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_2c_relu (Activation) (None, 512, 48, 48) 0 add_22[0][0]
__________________________________________________________________________________________________
block_2d_conv_1 (Conv2D) (None, 128, 48, 48) 65536 block_2c_relu[0][0]
__________________________________________________________________________________________________
block_2d_bn_1 (BatchNormalizati (None, 128, 48, 48) 512 block_2d_conv_1[0][0]
__________________________________________________________________________________________________
block_2d_relu_1 (Activation) (None, 128, 48, 48) 0 block_2d_bn_1[0][0]
__________________________________________________________________________________________________
block_2d_conv_2 (Conv2D) (None, 128, 48, 48) 147456 block_2d_relu_1[0][0]
__________________________________________________________________________________________________
block_2d_bn_2 (BatchNormalizati (None, 128, 48, 48) 512 block_2d_conv_2[0][0]
__________________________________________________________________________________________________
block_2d_relu_2 (Activation) (None, 128, 48, 48) 0 block_2d_bn_2[0][0]
__________________________________________________________________________________________________
block_2d_conv_3 (Conv2D) (None, 512, 48, 48) 65536 block_2d_relu_2[0][0]
__________________________________________________________________________________________________
block_2d_conv_shortcut (Conv2D) (None, 512, 48, 48) 262144 block_2c_relu[0][0]
__________________________________________________________________________________________________
block_2d_bn_3 (BatchNormalizati (None, 512, 48, 48) 2048 block_2d_conv_3[0][0]
__________________________________________________________________________________________________
block_2d_bn_shortcut (BatchNorm (None, 512, 48, 48) 2048 block_2d_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_23 (Add) (None, 512, 48, 48) 0 block_2d_bn_3[0][0]
block_2d_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_2d_relu (Activation) (None, 512, 48, 48) 0 add_23[0][0]
__________________________________________________________________________________________________
block_3a_conv_1 (Conv2D) (None, 256, 24, 24) 131072 block_2d_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_1 (BatchNormalizati (None, 256, 24, 24) 1024 block_3a_conv_1[0][0]
__________________________________________________________________________________________________
block_3a_relu_1 (Activation) (None, 256, 24, 24) 0 block_3a_bn_1[0][0]
__________________________________________________________________________________________________
block_3a_conv_2 (Conv2D) (None, 256, 24, 24) 589824 block_3a_relu_1[0][0]
__________________________________________________________________________________________________
block_3a_bn_2 (BatchNormalizati (None, 256, 24, 24) 1024 block_3a_conv_2[0][0]
__________________________________________________________________________________________________
block_3a_relu_2 (Activation) (None, 256, 24, 24) 0 block_3a_bn_2[0][0]
__________________________________________________________________________________________________
block_3a_conv_3 (Conv2D) (None, 1024, 24, 24) 262144 block_3a_relu_2[0][0]
__________________________________________________________________________________________________
block_3a_conv_shortcut (Conv2D) (None, 1024, 24, 24) 524288 block_2d_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_3 (BatchNormalizati (None, 1024, 24, 24) 4096 block_3a_conv_3[0][0]
__________________________________________________________________________________________________
block_3a_bn_shortcut (BatchNorm (None, 1024, 24, 24) 4096 block_3a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_24 (Add) (None, 1024, 24, 24) 0 block_3a_bn_3[0][0]
block_3a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3a_relu (Activation) (None, 1024, 24, 24) 0 add_24[0][0]
__________________________________________________________________________________________________
block_3b_conv_1 (Conv2D) (None, 256, 24, 24) 262144 block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_bn_1 (BatchNormalizati (None, 256, 24, 24) 1024 block_3b_conv_1[0][0]
__________________________________________________________________________________________________
block_3b_relu_1 (Activation) (None, 256, 24, 24) 0 block_3b_bn_1[0][0]
__________________________________________________________________________________________________
block_3b_conv_2 (Conv2D) (None, 256, 24, 24) 589824 block_3b_relu_1[0][0]
__________________________________________________________________________________________________
block_3b_bn_2 (BatchNormalizati (None, 256, 24, 24) 1024 block_3b_conv_2[0][0]
__________________________________________________________________________________________________
block_3b_relu_2 (Activation) (None, 256, 24, 24) 0 block_3b_bn_2[0][0]
__________________________________________________________________________________________________
block_3b_conv_3 (Conv2D) (None, 1024, 24, 24) 262144 block_3b_relu_2[0][0]
__________________________________________________________________________________________________
block_3b_conv_shortcut (Conv2D) (None, 1024, 24, 24) 1048576 block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_bn_3 (BatchNormalizati (None, 1024, 24, 24) 4096 block_3b_conv_3[0][0]
__________________________________________________________________________________________________
block_3b_bn_shortcut (BatchNorm (None, 1024, 24, 24) 4096 block_3b_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_25 (Add) (None, 1024, 24, 24) 0 block_3b_bn_3[0][0]
block_3b_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3b_relu (Activation) (None, 1024, 24, 24) 0 add_25[0][0]
__________________________________________________________________________________________________
block_3c_conv_1 (Conv2D) (None, 256, 24, 24) 262144 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_3c_bn_1 (BatchNormalizati (None, 256, 24, 24) 1024 block_3c_conv_1[0][0]
__________________________________________________________________________________________________
block_3c_relu_1 (Activation) (None, 256, 24, 24) 0 block_3c_bn_1[0][0]
__________________________________________________________________________________________________
block_3c_conv_2 (Conv2D) (None, 256, 24, 24) 589824 block_3c_relu_1[0][0]
__________________________________________________________________________________________________
block_3c_bn_2 (BatchNormalizati (None, 256, 24, 24) 1024 block_3c_conv_2[0][0]
__________________________________________________________________________________________________
block_3c_relu_2 (Activation) (None, 256, 24, 24) 0 block_3c_bn_2[0][0]
__________________________________________________________________________________________________
block_3c_conv_3 (Conv2D) (None, 1024, 24, 24) 262144 block_3c_relu_2[0][0]
__________________________________________________________________________________________________
block_3c_conv_shortcut (Conv2D) (None, 1024, 24, 24) 1048576 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_3c_bn_3 (BatchNormalizati (None, 1024, 24, 24) 4096 block_3c_conv_3[0][0]
__________________________________________________________________________________________________
block_3c_bn_shortcut (BatchNorm (None, 1024, 24, 24) 4096 block_3c_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_26 (Add) (None, 1024, 24, 24) 0 block_3c_bn_3[0][0]
block_3c_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3c_relu (Activation) (None, 1024, 24, 24) 0 add_26[0][0]
__________________________________________________________________________________________________
block_3d_conv_1 (Conv2D) (None, 256, 24, 24) 262144 block_3c_relu[0][0]
__________________________________________________________________________________________________
block_3d_bn_1 (BatchNormalizati (None, 256, 24, 24) 1024 block_3d_conv_1[0][0]
__________________________________________________________________________________________________
block_3d_relu_1 (Activation) (None, 256, 24, 24) 0 block_3d_bn_1[0][0]
__________________________________________________________________________________________________
block_3d_conv_2 (Conv2D) (None, 256, 24, 24) 589824 block_3d_relu_1[0][0]
__________________________________________________________________________________________________
block_3d_bn_2 (BatchNormalizati (None, 256, 24, 24) 1024 block_3d_conv_2[0][0]
__________________________________________________________________________________________________
block_3d_relu_2 (Activation) (None, 256, 24, 24) 0 block_3d_bn_2[0][0]
__________________________________________________________________________________________________
block_3d_conv_3 (Conv2D) (None, 1024, 24, 24) 262144 block_3d_relu_2[0][0]
__________________________________________________________________________________________________
block_3d_conv_shortcut (Conv2D) (None, 1024, 24, 24) 1048576 block_3c_relu[0][0]
__________________________________________________________________________________________________
block_3d_bn_3 (BatchNormalizati (None, 1024, 24, 24) 4096 block_3d_conv_3[0][0]
__________________________________________________________________________________________________
block_3d_bn_shortcut (BatchNorm (None, 1024, 24, 24) 4096 block_3d_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_27 (Add) (None, 1024, 24, 24) 0 block_3d_bn_3[0][0]
block_3d_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3d_relu (Activation) (None, 1024, 24, 24) 0 add_27[0][0]
__________________________________________________________________________________________________
block_3e_conv_1 (Conv2D) (None, 256, 24, 24) 262144 block_3d_relu[0][0]
__________________________________________________________________________________________________
block_3e_bn_1 (BatchNormalizati (None, 256, 24, 24) 1024 block_3e_conv_1[0][0]
__________________________________________________________________________________________________
block_3e_relu_1 (Activation) (None, 256, 24, 24) 0 block_3e_bn_1[0][0]
__________________________________________________________________________________________________
block_3e_conv_2 (Conv2D) (None, 256, 24, 24) 589824 block_3e_relu_1[0][0]
__________________________________________________________________________________________________
block_3e_bn_2 (BatchNormalizati (None, 256, 24, 24) 1024 block_3e_conv_2[0][0]
__________________________________________________________________________________________________
block_3e_relu_2 (Activation) (None, 256, 24, 24) 0 block_3e_bn_2[0][0]
__________________________________________________________________________________________________
block_3e_conv_3 (Conv2D) (None, 1024, 24, 24) 262144 block_3e_relu_2[0][0]
__________________________________________________________________________________________________
block_3e_conv_shortcut (Conv2D) (None, 1024, 24, 24) 1048576 block_3d_relu[0][0]
__________________________________________________________________________________________________
block_3e_bn_3 (BatchNormalizati (None, 1024, 24, 24) 4096 block_3e_conv_3[0][0]
__________________________________________________________________________________________________
block_3e_bn_shortcut (BatchNorm (None, 1024, 24, 24) 4096 block_3e_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_28 (Add) (None, 1024, 24, 24) 0 block_3e_bn_3[0][0]
block_3e_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3e_relu (Activation) (None, 1024, 24, 24) 0 add_28[0][0]
__________________________________________________________________________________________________
block_3f_conv_1 (Conv2D) (None, 256, 24, 24) 262144 block_3e_relu[0][0]
__________________________________________________________________________________________________
block_3f_bn_1 (BatchNormalizati (None, 256, 24, 24) 1024 block_3f_conv_1[0][0]
__________________________________________________________________________________________________
block_3f_relu_1 (Activation) (None, 256, 24, 24) 0 block_3f_bn_1[0][0]
__________________________________________________________________________________________________
block_3f_conv_2 (Conv2D) (None, 256, 24, 24) 589824 block_3f_relu_1[0][0]
__________________________________________________________________________________________________
block_3f_bn_2 (BatchNormalizati (None, 256, 24, 24) 1024 block_3f_conv_2[0][0]
__________________________________________________________________________________________________
block_3f_relu_2 (Activation) (None, 256, 24, 24) 0 block_3f_bn_2[0][0]
__________________________________________________________________________________________________
block_3f_conv_3 (Conv2D) (None, 1024, 24, 24) 262144 block_3f_relu_2[0][0]
__________________________________________________________________________________________________
block_3f_conv_shortcut (Conv2D) (None, 1024, 24, 24) 1048576 block_3e_relu[0][0]
__________________________________________________________________________________________________
block_3f_bn_3 (BatchNormalizati (None, 1024, 24, 24) 4096 block_3f_conv_3[0][0]
__________________________________________________________________________________________________
block_3f_bn_shortcut (BatchNorm (None, 1024, 24, 24) 4096 block_3f_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_29 (Add) (None, 1024, 24, 24) 0 block_3f_bn_3[0][0]
block_3f_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3f_relu (Activation) (None, 1024, 24, 24) 0 add_29[0][0]
__________________________________________________________________________________________________
block_4a_conv_1 (Conv2D) (None, 512, 24, 24) 524288 block_3f_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_1 (BatchNormalizati (None, 512, 24, 24) 2048 block_4a_conv_1[0][0]
__________________________________________________________________________________________________
block_4a_relu_1 (Activation) (None, 512, 24, 24) 0 block_4a_bn_1[0][0]
__________________________________________________________________________________________________
block_4a_conv_2 (Conv2D) (None, 512, 24, 24) 2359296 block_4a_relu_1[0][0]
__________________________________________________________________________________________________
block_4a_bn_2 (BatchNormalizati (None, 512, 24, 24) 2048 block_4a_conv_2[0][0]
__________________________________________________________________________________________________
block_4a_relu_2 (Activation) (None, 512, 24, 24) 0 block_4a_bn_2[0][0]
__________________________________________________________________________________________________
block_4a_conv_3 (Conv2D) (None, 2048, 24, 24) 1048576 block_4a_relu_2[0][0]
__________________________________________________________________________________________________
block_4a_conv_shortcut (Conv2D) (None, 2048, 24, 24) 2097152 block_3f_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_3 (BatchNormalizati (None, 2048, 24, 24) 8192 block_4a_conv_3[0][0]
__________________________________________________________________________________________________
block_4a_bn_shortcut (BatchNorm (None, 2048, 24, 24) 8192 block_4a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_30 (Add) (None, 2048, 24, 24) 0 block_4a_bn_3[0][0]
block_4a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_4a_relu (Activation) (None, 2048, 24, 24) 0 add_30[0][0]
__________________________________________________________________________________________________
block_4b_conv_1 (Conv2D) (None, 512, 24, 24) 1048576 block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_bn_1 (BatchNormalizati (None, 512, 24, 24) 2048 block_4b_conv_1[0][0]
__________________________________________________________________________________________________
block_4b_relu_1 (Activation) (None, 512, 24, 24) 0 block_4b_bn_1[0][0]
__________________________________________________________________________________________________
block_4b_conv_2 (Conv2D) (None, 512, 24, 24) 2359296 block_4b_relu_1[0][0]
__________________________________________________________________________________________________
block_4b_bn_2 (BatchNormalizati (None, 512, 24, 24) 2048 block_4b_conv_2[0][0]
__________________________________________________________________________________________________
block_4b_relu_2 (Activation) (None, 512, 24, 24) 0 block_4b_bn_2[0][0]
__________________________________________________________________________________________________
block_4b_conv_3 (Conv2D) (None, 2048, 24, 24) 1048576 block_4b_relu_2[0][0]
__________________________________________________________________________________________________
block_4b_conv_shortcut (Conv2D) (None, 2048, 24, 24) 4194304 block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_bn_3 (BatchNormalizati (None, 2048, 24, 24) 8192 block_4b_conv_3[0][0]
__________________________________________________________________________________________________
block_4b_bn_shortcut (BatchNorm (None, 2048, 24, 24) 8192 block_4b_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_31 (Add) (None, 2048, 24, 24) 0 block_4b_bn_3[0][0]
block_4b_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_4b_relu (Activation) (None, 2048, 24, 24) 0 add_31[0][0]
__________________________________________________________________________________________________
block_4c_conv_1 (Conv2D) (None, 512, 24, 24) 1048576 block_4b_relu[0][0]
__________________________________________________________________________________________________
block_4c_bn_1 (BatchNormalizati (None, 512, 24, 24) 2048 block_4c_conv_1[0][0]
__________________________________________________________________________________________________
block_4c_relu_1 (Activation) (None, 512, 24, 24) 0 block_4c_bn_1[0][0]
__________________________________________________________________________________________________
block_4c_conv_2 (Conv2D) (None, 512, 24, 24) 2359296 block_4c_relu_1[0][0]
__________________________________________________________________________________________________
block_4c_bn_2 (BatchNormalizati (None, 512, 24, 24) 2048 block_4c_conv_2[0][0]
__________________________________________________________________________________________________
block_4c_relu_2 (Activation) (None, 512, 24, 24) 0 block_4c_bn_2[0][0]
__________________________________________________________________________________________________
block_4c_conv_3 (Conv2D) (None, 2048, 24, 24) 1048576 block_4c_relu_2[0][0]
__________________________________________________________________________________________________
block_4c_conv_shortcut (Conv2D) (None, 2048, 24, 24) 4194304 block_4b_relu[0][0]
__________________________________________________________________________________________________
block_4c_bn_3 (BatchNormalizati (None, 2048, 24, 24) 8192 block_4c_conv_3[0][0]
__________________________________________________________________________________________________
block_4c_bn_shortcut (BatchNorm (None, 2048, 24, 24) 8192 block_4c_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_32 (Add) (None, 2048, 24, 24) 0 block_4c_bn_3[0][0]
block_4c_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_4c_relu (Activation) (None, 2048, 24, 24) 0 add_32[0][0]
__________________________________________________________________________________________________
yolo_spp_pool_1 (MaxPooling2D) (None, 2048, 24, 24) 0 block_4c_relu[0][0]
__________________________________________________________________________________________________
yolo_spp_pool_2 (MaxPooling2D) (None, 2048, 24, 24) 0 block_4c_relu[0][0]
__________________________________________________________________________________________________
yolo_spp_pool_3 (MaxPooling2D) (None, 2048, 24, 24) 0 block_4c_relu[0][0]
__________________________________________________________________________________________________
yolo_spp_concat (Concatenate) (None, 8192, 24, 24) 0 yolo_spp_pool_1[0][0]
yolo_spp_pool_2[0][0]
yolo_spp_pool_3[0][0]
block_4c_relu[0][0]
__________________________________________________________________________________________________
yolo_spp_conv (Conv2D) (None, 512, 24, 24) 4194304 yolo_spp_concat[0][0]
__________________________________________________________________________________________________
yolo_spp_conv_bn (BatchNormaliz (None, 512, 24, 24) 2048 yolo_spp_conv[0][0]
__________________________________________________________________________________________________
yolo_spp_conv_lrelu (LeakyReLU) (None, 512, 24, 24) 0 yolo_spp_conv_bn[0][0]
__________________________________________________________________________________________________
yolo_expand_conv1 (Conv2D) (None, 1024, 12, 12) 4718592 yolo_spp_conv_lrelu[0][0]
__________________________________________________________________________________________________
yolo_expand_conv1_bn (BatchNorm (None, 1024, 12, 12) 4096 yolo_expand_conv1[0][0]
__________________________________________________________________________________________________
yolo_expand_conv1_lrelu (LeakyR (None, 1024, 12, 12) 0 yolo_expand_conv1_bn[0][0]
__________________________________________________________________________________________________
yolo_conv1_1 (Conv2D) (None, 512, 12, 12) 524288 yolo_expand_conv1_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv1_1_bn (BatchNormaliza (None, 512, 12, 12) 2048 yolo_conv1_1[0][0]
__________________________________________________________________________________________________
yolo_conv1_1_lrelu (LeakyReLU) (None, 512, 12, 12) 0 yolo_conv1_1_bn[0][0]
__________________________________________________________________________________________________
yolo_conv1_2 (Conv2D) (None, 1024, 12, 12) 4718592 yolo_conv1_1_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv1_2_bn (BatchNormaliza (None, 1024, 12, 12) 4096 yolo_conv1_2[0][0]
__________________________________________________________________________________________________
yolo_conv1_2_lrelu (LeakyReLU) (None, 1024, 12, 12) 0 yolo_conv1_2_bn[0][0]
__________________________________________________________________________________________________
yolo_conv1_3 (Conv2D) (None, 512, 12, 12) 524288 yolo_conv1_2_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv1_3_bn (BatchNormaliza (None, 512, 12, 12) 2048 yolo_conv1_3[0][0]
__________________________________________________________________________________________________
yolo_conv1_3_lrelu (LeakyReLU) (None, 512, 12, 12) 0 yolo_conv1_3_bn[0][0]
__________________________________________________________________________________________________
yolo_conv1_4 (Conv2D) (None, 1024, 12, 12) 4718592 yolo_conv1_3_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv1_4_bn (BatchNormaliza (None, 1024, 12, 12) 4096 yolo_conv1_4[0][0]
__________________________________________________________________________________________________
yolo_conv1_4_lrelu (LeakyReLU) (None, 1024, 12, 12) 0 yolo_conv1_4_bn[0][0]
__________________________________________________________________________________________________
yolo_conv1_5 (Conv2D) (None, 512, 12, 12) 524288 yolo_conv1_4_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv1_5_bn (BatchNormaliza (None, 512, 12, 12) 2048 yolo_conv1_5[0][0]
__________________________________________________________________________________________________
yolo_conv1_5_lrelu (LeakyReLU) (None, 512, 12, 12) 0 yolo_conv1_5_bn[0][0]
__________________________________________________________________________________________________
yolo_conv2 (Conv2D) (None, 256, 12, 12) 131072 yolo_conv1_5_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv2_bn (BatchNormalizati (None, 256, 12, 12) 1024 yolo_conv2[0][0]
__________________________________________________________________________________________________
yolo_conv2_lrelu (LeakyReLU) (None, 256, 12, 12) 0 yolo_conv2_bn[0][0]
__________________________________________________________________________________________________
upsample0 (UpSampling2D) (None, 256, 24, 24) 0 yolo_conv2_lrelu[0][0]
__________________________________________________________________________________________________
concatenate_3 (Concatenate) (None, 768, 24, 24) 0 upsample0[0][0]
block_4c_relu_2[0][0]
__________________________________________________________________________________________________
yolo_conv3_1 (Conv2D) (None, 256, 24, 24) 196608 concatenate_3[0][0]
__________________________________________________________________________________________________
yolo_conv3_1_bn (BatchNormaliza (None, 256, 24, 24) 1024 yolo_conv3_1[0][0]
__________________________________________________________________________________________________
yolo_conv3_1_lrelu (LeakyReLU) (None, 256, 24, 24) 0 yolo_conv3_1_bn[0][0]
__________________________________________________________________________________________________
yolo_conv3_2 (Conv2D) (None, 512, 24, 24) 1179648 yolo_conv3_1_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv3_2_bn (BatchNormaliza (None, 512, 24, 24) 2048 yolo_conv3_2[0][0]
__________________________________________________________________________________________________
yolo_conv3_2_lrelu (LeakyReLU) (None, 512, 24, 24) 0 yolo_conv3_2_bn[0][0]
__________________________________________________________________________________________________
yolo_conv3_3 (Conv2D) (None, 256, 24, 24) 131072 yolo_conv3_2_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv3_3_bn (BatchNormaliza (None, 256, 24, 24) 1024 yolo_conv3_3[0][0]
__________________________________________________________________________________________________
yolo_conv3_3_lrelu (LeakyReLU) (None, 256, 24, 24) 0 yolo_conv3_3_bn[0][0]
__________________________________________________________________________________________________
yolo_conv3_4 (Conv2D) (None, 512, 24, 24) 1179648 yolo_conv3_3_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv3_4_bn (BatchNormaliza (None, 512, 24, 24) 2048 yolo_conv3_4[0][0]
__________________________________________________________________________________________________
yolo_conv3_4_lrelu (LeakyReLU) (None, 512, 24, 24) 0 yolo_conv3_4_bn[0][0]
__________________________________________________________________________________________________
yolo_conv3_5 (Conv2D) (None, 256, 24, 24) 131072 yolo_conv3_4_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv3_5_bn (BatchNormaliza (None, 256, 24, 24) 1024 yolo_conv3_5[0][0]
__________________________________________________________________________________________________
yolo_conv3_5_lrelu (LeakyReLU) (None, 256, 24, 24) 0 yolo_conv3_5_bn[0][0]
__________________________________________________________________________________________________
yolo_conv4 (Conv2D) (None, 128, 24, 24) 32768 yolo_conv3_5_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv4_bn (BatchNormalizati (None, 128, 24, 24) 512 yolo_conv4[0][0]
__________________________________________________________________________________________________
yolo_conv4_lrelu (LeakyReLU) (None, 128, 24, 24) 0 yolo_conv4_bn[0][0]
__________________________________________________________________________________________________
upsample1 (UpSampling2D) (None, 128, 48, 48) 0 yolo_conv4_lrelu[0][0]
__________________________________________________________________________________________________
expand_upsample (UpSampling2D) (None, 256, 48, 48) 0 block_3f_relu_2[0][0]
__________________________________________________________________________________________________
concatenate_4 (Concatenate) (None, 384, 48, 48) 0 upsample1[0][0]
expand_upsample[0][0]
__________________________________________________________________________________________________
yolo_conv5_1 (Conv2D) (None, 128, 48, 48) 49152 concatenate_4[0][0]
__________________________________________________________________________________________________
yolo_conv5_1_bn (BatchNormaliza (None, 128, 48, 48) 512 yolo_conv5_1[0][0]
__________________________________________________________________________________________________
yolo_conv5_1_lrelu (LeakyReLU) (None, 128, 48, 48) 0 yolo_conv5_1_bn[0][0]
__________________________________________________________________________________________________
yolo_conv5_2 (Conv2D) (None, 256, 48, 48) 294912 yolo_conv5_1_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv5_2_bn (BatchNormaliza (None, 256, 48, 48) 1024 yolo_conv5_2[0][0]
__________________________________________________________________________________________________
yolo_conv5_2_lrelu (LeakyReLU) (None, 256, 48, 48) 0 yolo_conv5_2_bn[0][0]
__________________________________________________________________________________________________
yolo_conv5_3 (Conv2D) (None, 128, 48, 48) 32768 yolo_conv5_2_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv5_3_bn (BatchNormaliza (None, 128, 48, 48) 512 yolo_conv5_3[0][0]
__________________________________________________________________________________________________
yolo_conv5_3_lrelu (LeakyReLU) (None, 128, 48, 48) 0 yolo_conv5_3_bn[0][0]
__________________________________________________________________________________________________
yolo_conv5_4 (Conv2D) (None, 256, 48, 48) 294912 yolo_conv5_3_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv5_4_bn (BatchNormaliza (None, 256, 48, 48) 1024 yolo_conv5_4[0][0]
__________________________________________________________________________________________________
yolo_conv5_4_lrelu (LeakyReLU) (None, 256, 48, 48) 0 yolo_conv5_4_bn[0][0]
__________________________________________________________________________________________________
yolo_conv5_5 (Conv2D) (None, 128, 48, 48) 32768 yolo_conv5_4_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv5_5_bn (BatchNormaliza (None, 128, 48, 48) 512 yolo_conv5_5[0][0]
__________________________________________________________________________________________________
yolo_conv5_5_lrelu (LeakyReLU) (None, 128, 48, 48) 0 yolo_conv5_5_bn[0][0]
__________________________________________________________________________________________________
yolo_conv1_6 (Conv2D) (None, 1024, 12, 12) 4718592 yolo_conv1_5_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv3_6 (Conv2D) (None, 512, 24, 24) 1179648 yolo_conv3_5_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv5_6 (Conv2D) (None, 256, 48, 48) 294912 yolo_conv5_5_lrelu[0][0]
__________________________________________________________________________________________________
yolo_conv1_6_bn (BatchNormaliza (None, 1024, 12, 12) 4096 yolo_conv1_6[0][0]
__________________________________________________________________________________________________
yolo_conv3_6_bn (BatchNormaliza (None, 512, 24, 24) 2048 yolo_conv3_6[0][0]
__________________________________________________________________________________________________
yolo_conv5_6_bn (BatchNormaliza (None, 256, 48, 48) 1024 yolo_conv5_6[0][0]
__________________________________________________________________________________________________
yolo_conv1_6_lrelu (LeakyReLU) (None, 1024, 12, 12) 0 yolo_conv1_6_bn[0][0]
__________________________________________________________________________________________________
yolo_conv3_6_lrelu (LeakyReLU) (None, 512, 24, 24) 0 yolo_conv3_6_bn[0][0]
__________________________________________________________________________________________________
yolo_conv5_6_lrelu (LeakyReLU) (None, 256, 48, 48) 0 yolo_conv5_6_bn[0][0]
__________________________________________________________________________________________________
conv_big_object (Conv2D) (None, 24, 12, 12) 24600 yolo_conv1_6_lrelu[0][0]
__________________________________________________________________________________________________
conv_mid_object (Conv2D) (None, 24, 24, 24) 12312 yolo_conv3_6_lrelu[0][0]
__________________________________________________________________________________________________
conv_sm_object (Conv2D) (None, 24, 48, 48) 6168 yolo_conv5_6_lrelu[0][0]
__________________________________________________________________________________________________
bg_permute (Permute) (None, 12, 12, 24) 0 conv_big_object[0][0]
__________________________________________________________________________________________________
md_permute (Permute) (None, 24, 24, 24) 0 conv_mid_object[0][0]
__________________________________________________________________________________________________
sm_permute (Permute) (None, 48, 48, 24) 0 conv_sm_object[0][0]
__________________________________________________________________________________________________
bg_reshape (Reshape) (None, 432, 8) 0 bg_permute[0][0]
__________________________________________________________________________________________________
md_reshape (Reshape) (None, 1728, 8) 0 md_permute[0][0]
__________________________________________________________________________________________________
sm_reshape (Reshape) (None, 6912, 8) 0 sm_permute[0][0]
__________________________________________________________________________________________________
bg_anchor (YOLOAnchorBox) (None, 432, 6) 0 conv_big_object[0][0]
__________________________________________________________________________________________________
bg_bbox_processor (BBoxPostProc (None, 432, 8) 0 bg_reshape[0][0]
__________________________________________________________________________________________________
md_anchor (YOLOAnchorBox) (None, 1728, 6) 0 conv_mid_object[0][0]
__________________________________________________________________________________________________
md_bbox_processor (BBoxPostProc (None, 1728, 8) 0 md_reshape[0][0]
__________________________________________________________________________________________________
sm_anchor (YOLOAnchorBox) (None, 6912, 6) 0 conv_sm_object[0][0]
__________________________________________________________________________________________________
sm_bbox_processor (BBoxPostProc (None, 6912, 8) 0 sm_reshape[0][0]
__________________________________________________________________________________________________
encoded_bg (Concatenate) (None, 432, 14) 0 bg_anchor[0][0]
bg_bbox_processor[0][0]
__________________________________________________________________________________________________
encoded_md (Concatenate) (None, 1728, 14) 0 md_anchor[0][0]
md_bbox_processor[0][0]
__________________________________________________________________________________________________
encoded_sm (Concatenate) (None, 6912, 14) 0 sm_anchor[0][0]
sm_bbox_processor[0][0]
__________________________________________________________________________________________________
encoded_detections (Concatenate (None, 9072, 14) 0 encoded_bg[0][0]
encoded_md[0][0]
encoded_sm[0][0]
==================================================================================================
Total params: 68,040,712
Trainable params: 67,945,096
Non-trainable params: 95,616
__________________________________________________________________________________________________
2021-07-02 12:23:20,990 [INFO] __main__: Number of images in the training dataset: 10
Epoch 1/1
2/10 [=====>........................] - ETA: 34:42 - loss: 96.4671 /usr/local/lib/python3.6/dist-packages/keras/callbacks.py:122: UserWarning: Method on_batch_end() is slow compared to the batch update (3.052041). Check your callbacks.
% delta_t_median)
10/10 [==============================] - 522s 52s/step - loss: 92.5794
Epoch 00001: saving model to /workspace/tlt-experiments/yolo_v4/experiment_dir_unpruned/weights/yolov4_resnet50_epoch_001.tlt