2022-09-20 10:41:15,038 [INFO] root: Registry: ['nvcr.io'] 2022-09-20 10:41:15,176 [INFO] tlt.components.instance_handler.local_instance: Running command in container: nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.5-py3 Using TensorFlow backend. WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them. /usr/local/lib/python3.6/dist-packages/requests/__init__.py:91: RequestsDependencyWarning: urllib3 (1.26.5) or chardet (3.0.4) doesn't match a supported version! RequestsDependencyWarning) Using TensorFlow backend. /usr/local/lib/python3.6/dist-packages/numba/cuda/envvars.py:17: NumbaWarning: Environment variables with the 'NUMBAPRO' prefix are deprecated and consequently ignored, found use of NUMBAPRO_NVVM=/usr/local/cuda/nvvm/lib64/libnvvm.so. For more information about alternatives visit: ('http://numba.pydata.org/numba-doc/latest/cuda/overview.html', '#cudatoolkit-lookup') warnings.warn(errors.NumbaWarning(msg)) /usr/local/lib/python3.6/dist-packages/numba/cuda/envvars.py:17: NumbaWarning: Environment variables with the 'NUMBAPRO' prefix are deprecated and consequently ignored, found use of NUMBAPRO_LIBDEVICE=/usr/local/cuda/nvvm/libdevice/. For more information about alternatives visit: ('http://numba.pydata.org/numba-doc/latest/cuda/overview.html', '#cudatoolkit-lookup') warnings.warn(errors.NumbaWarning(msg)) 2022-09-20 02:41:22,734 [INFO] iva.common.logging.logging: Log file already exists at /workspace/tao_unet/unet/export_640_640/fp32/status.json 2022-09-20 02:41:22,734 [INFO] root: Building exporter object. 2022-09-20 02:41:22,735 [INFO] iva.unet.spec_handler.spec_loader: Merging specification from /workspace/tao_unet/specs/unet_train_resnet_unet_isbi.txt 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 0: Train Id 0 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 1: Train Id 1 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 2: Train Id 2 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 3: Train Id 3 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 4: Train Id 4 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 5: Train Id 5 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 6: Train Id 6 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 7: Train Id 7 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 8: Train Id 8 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 9: Train Id 9 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 10: Train Id 10 2022-09-20 02:41:22,739 [INFO] iva.unet.model.utilities: Label Id 11: Train Id 11 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 12: Train Id 12 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 13: Train Id 13 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 14: Train Id 14 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 15: Train Id 15 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 16: Train Id 16 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 17: Train Id 17 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 18: Train Id 18 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 19: Train Id 19 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 20: Train Id 20 2022-09-20 02:41:22,740 [INFO] iva.unet.model.utilities: Label Id 21: Train Id 21 2022-09-20 02:41:22,740 [INFO] iva.unet.model.model_io: Loading weights from /workspace/tao_unet/unet/isbi_experiment_unpruned/640_640/weights/model.tlt model.ckpt-109500.meta __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_1 (InputLayer) (None, 3, 640, 640) 0 __________________________________________________________________________________________________ conv1 (Conv2D) (None, 64, 320, 320) 9472 input_1[0][0] __________________________________________________________________________________________________ activation_1 (Activation) (None, 64, 320, 320) 0 conv1[0][0] __________________________________________________________________________________________________ block_1a_conv_1 (Conv2D) (None, 64, 160, 160) 36928 activation_1[0][0] __________________________________________________________________________________________________ block_1a_relu_1 (Activation) (None, 64, 160, 160) 0 block_1a_conv_1[0][0] __________________________________________________________________________________________________ block_1a_conv_2 (Conv2D) (None, 64, 160, 160) 36928 block_1a_relu_1[0][0] __________________________________________________________________________________________________ block_1a_conv_shortcut (Conv2D) (None, 64, 160, 160) 4160 activation_1[0][0] __________________________________________________________________________________________________ add_1 (Add) (None, 64, 160, 160) 0 block_1a_conv_2[0][0] block_1a_conv_shortcut[0][0] __________________________________________________________________________________________________ block_1a_relu (Activation) (None, 64, 160, 160) 0 add_1[0][0] __________________________________________________________________________________________________ block_1b_conv_1 (Conv2D) (None, 64, 160, 160) 36928 block_1a_relu[0][0] __________________________________________________________________________________________________ block_1b_relu_1 (Activation) (None, 64, 160, 160) 0 block_1b_conv_1[0][0] __________________________________________________________________________________________________ block_1b_conv_2 (Conv2D) (None, 64, 160, 160) 36928 block_1b_relu_1[0][0] __________________________________________________________________________________________________ block_1b_conv_shortcut (Conv2D) (None, 64, 160, 160) 4160 block_1a_relu[0][0] __________________________________________________________________________________________________ add_2 (Add) (None, 64, 160, 160) 0 block_1b_conv_2[0][0] block_1b_conv_shortcut[0][0] __________________________________________________________________________________________________ block_1b_relu (Activation) (None, 64, 160, 160) 0 add_2[0][0] __________________________________________________________________________________________________ block_2a_conv_1 (Conv2D) (None, 128, 80, 80) 73856 block_1b_relu[0][0] __________________________________________________________________________________________________ block_2a_relu_1 (Activation) (None, 128, 80, 80) 0 block_2a_conv_1[0][0] __________________________________________________________________________________________________ block_2a_conv_2 (Conv2D) (None, 128, 80, 80) 147584 block_2a_relu_1[0][0] __________________________________________________________________________________________________ block_2a_conv_shortcut (Conv2D) (None, 128, 80, 80) 8320 block_1b_relu[0][0] __________________________________________________________________________________________________ add_3 (Add) (None, 128, 80, 80) 0 block_2a_conv_2[0][0] block_2a_conv_shortcut[0][0] __________________________________________________________________________________________________ block_2a_relu (Activation) (None, 128, 80, 80) 0 add_3[0][0] __________________________________________________________________________________________________ block_2b_conv_1 (Conv2D) (None, 128, 80, 80) 147584 block_2a_relu[0][0] __________________________________________________________________________________________________ block_2b_relu_1 (Activation) (None, 128, 80, 80) 0 block_2b_conv_1[0][0] __________________________________________________________________________________________________ block_2b_conv_2 (Conv2D) (None, 128, 80, 80) 147584 block_2b_relu_1[0][0] __________________________________________________________________________________________________ block_2b_conv_shortcut (Conv2D) (None, 128, 80, 80) 16512 block_2a_relu[0][0] __________________________________________________________________________________________________ add_4 (Add) (None, 128, 80, 80) 0 block_2b_conv_2[0][0] block_2b_conv_shortcut[0][0] __________________________________________________________________________________________________ block_2b_relu (Activation) (None, 128, 80, 80) 0 add_4[0][0] __________________________________________________________________________________________________ block_3a_conv_1 (Conv2D) (None, 256, 40, 40) 295168 block_2b_relu[0][0] __________________________________________________________________________________________________ block_3a_relu_1 (Activation) (None, 256, 40, 40) 0 block_3a_conv_1[0][0] __________________________________________________________________________________________________ block_3a_conv_2 (Conv2D) (None, 256, 40, 40) 590080 block_3a_relu_1[0][0] __________________________________________________________________________________________________ block_3a_conv_shortcut (Conv2D) (None, 256, 40, 40) 33024 block_2b_relu[0][0] __________________________________________________________________________________________________ add_5 (Add) (None, 256, 40, 40) 0 block_3a_conv_2[0][0] block_3a_conv_shortcut[0][0] __________________________________________________________________________________________________ block_3a_relu (Activation) (None, 256, 40, 40) 0 add_5[0][0] __________________________________________________________________________________________________ block_3b_conv_1 (Conv2D) (None, 256, 40, 40) 590080 block_3a_relu[0][0] __________________________________________________________________________________________________ block_3b_relu_1 (Activation) (None, 256, 40, 40) 0 block_3b_conv_1[0][0] __________________________________________________________________________________________________ block_3b_conv_2 (Conv2D) (None, 256, 40, 40) 590080 block_3b_relu_1[0][0] __________________________________________________________________________________________________ block_3b_conv_shortcut (Conv2D) (None, 256, 40, 40) 65792 block_3a_relu[0][0] __________________________________________________________________________________________________ add_6 (Add) (None, 256, 40, 40) 0 block_3b_conv_2[0][0] block_3b_conv_shortcut[0][0] __________________________________________________________________________________________________ block_3b_relu (Activation) (None, 256, 40, 40) 0 add_6[0][0] __________________________________________________________________________________________________ block_4a_conv_1 (Conv2D) (None, 512, 40, 40) 1180160 block_3b_relu[0][0] __________________________________________________________________________________________________ block_4a_relu_1 (Activation) (None, 512, 40, 40) 0 block_4a_conv_1[0][0] __________________________________________________________________________________________________ block_4a_conv_2 (Conv2D) (None, 512, 40, 40) 2359808 block_4a_relu_1[0][0] __________________________________________________________________________________________________ block_4a_conv_shortcut (Conv2D) (None, 512, 40, 40) 131584 block_3b_relu[0][0] __________________________________________________________________________________________________ add_7 (Add) (None, 512, 40, 40) 0 block_4a_conv_2[0][0] block_4a_conv_shortcut[0][0] __________________________________________________________________________________________________ block_4a_relu (Activation) (None, 512, 40, 40) 0 add_7[0][0] __________________________________________________________________________________________________ block_4b_conv_1 (Conv2D) (None, 512, 40, 40) 2359808 block_4a_relu[0][0] __________________________________________________________________________________________________ block_4b_relu_1 (Activation) (None, 512, 40, 40) 0 block_4b_conv_1[0][0] __________________________________________________________________________________________________ block_4b_conv_2 (Conv2D) (None, 512, 40, 40) 2359808 block_4b_relu_1[0][0] __________________________________________________________________________________________________ block_4b_conv_shortcut (Conv2D) (None, 512, 40, 40) 262656 block_4a_relu[0][0] __________________________________________________________________________________________________ add_8 (Add) (None, 512, 40, 40) 0 block_4b_conv_2[0][0] block_4b_conv_shortcut[0][0] __________________________________________________________________________________________________ block_4b_relu (Activation) (None, 512, 40, 40) 0 add_8[0][0] __________________________________________________________________________________________________ conv2d_transpose_1 (Conv2DTrans (None, 256, 80, 80) 2097408 block_4b_relu[0][0] __________________________________________________________________________________________________ concatenate_1 (Concatenate) (None, 384, 80, 80) 0 conv2d_transpose_1[0][0] block_2b_relu[0][0] __________________________________________________________________________________________________ activation_2 (Activation) (None, 384, 80, 80) 0 concatenate_1[0][0] __________________________________________________________________________________________________ conv2d_1 (Conv2D) (None, 256, 80, 80) 884992 activation_2[0][0] __________________________________________________________________________________________________ activation_3 (Activation) (None, 256, 80, 80) 0 conv2d_1[0][0] __________________________________________________________________________________________________ conv2d_transpose_2 (Conv2DTrans (None, 128, 160, 160 524416 activation_3[0][0] __________________________________________________________________________________________________ concatenate_2 (Concatenate) (None, 192, 160, 160 0 conv2d_transpose_2[0][0] block_1b_relu[0][0] __________________________________________________________________________________________________ activation_4 (Activation) (None, 192, 160, 160 0 concatenate_2[0][0] __________________________________________________________________________________________________ conv2d_2 (Conv2D) (None, 128, 160, 160 221312 activation_4[0][0] __________________________________________________________________________________________________ activation_5 (Activation) (None, 128, 160, 160 0 conv2d_2[0][0] __________________________________________________________________________________________________ conv2d_transpose_3 (Conv2DTrans (None, 64, 320, 320) 131136 activation_5[0][0] __________________________________________________________________________________________________ concatenate_3 (Concatenate) (None, 128, 320, 320 0 conv2d_transpose_3[0][0] activation_1[0][0] __________________________________________________________________________________________________ activation_6 (Activation) (None, 128, 320, 320 0 concatenate_3[0][0] __________________________________________________________________________________________________ conv2d_3 (Conv2D) (None, 64, 320, 320) 73792 activation_6[0][0] __________________________________________________________________________________________________ activation_7 (Activation) (None, 64, 320, 320) 0 conv2d_3[0][0] __________________________________________________________________________________________________ conv2d_transpose_4 (Conv2DTrans (None, 64, 640, 640) 65600 activation_7[0][0] __________________________________________________________________________________________________ activation_8 (Activation) (None, 64, 640, 640) 0 conv2d_transpose_4[0][0] __________________________________________________________________________________________________ conv2d_4 (Conv2D) (None, 64, 640, 640) 36928 activation_8[0][0] __________________________________________________________________________________________________ activation_9 (Activation) (None, 64, 640, 640) 0 conv2d_4[0][0] __________________________________________________________________________________________________ conv2d_5 (Conv2D) (None, 22, 640, 640) 12694 activation_9[0][0] __________________________________________________________________________________________________ permute_1 (Permute) (None, 640, 640, 22) 0 conv2d_5[0][0] __________________________________________________________________________________________________ softmax_1 (Softmax) (None, 640, 640, 22) 0 permute_1[0][0] ================================================================================================== Total params: 15,573,270 Trainable params: 15,573,270 Non-trainable params: 0 __________________________________________________________________________________________________ 2022-09-20 02:41:26,090 [INFO] iva.unet.model.model_io: Loaded weights Successfully for Export 2022-09-20 02:41:26,090 [INFO] root: Exporting the model. 2022-09-20 02:41:26,091 [INFO] root: Using input nodes: ['input_1'] 2022-09-20 02:41:26,091 [INFO] root: Using output nodes: ['softmax_1'] 2022-09-20 02:41:26,091 [INFO] iva.common.export.keras_exporter: Using input nodes: ['input_1'] 2022-09-20 02:41:26,091 [INFO] iva.common.export.keras_exporter: Using output nodes: ['softmax_1'] 2022-09-20 02:41:29,373 [WARNING] tf2onnx.tfonnx: Argument verbose for process_tf_graph is deprecated. Please use --verbose option instead. 2022-09-20 02:41:29,373 [INFO] tf2onnx.tfonnx: Using tensorflow=1.15.5, onnx=1.8.1, tf2onnx=1.9.2/0f28b7 2022-09-20 02:41:29,373 [INFO] tf2onnx.tfonnx: Using opset 2022-09-20 02:41:30,058 [INFO] tf2onnx.tf_utils: Computed 76 values for constant folding 2022-09-20 02:41:30,266 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv1/kernel/read 2022-09-20 02:41:30,266 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv1/bias/read 2022-09-20 02:41:30,267 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1a_conv_1/kernel/read 2022-09-20 02:41:30,267 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1a_conv_1/bias/read 2022-09-20 02:41:30,267 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1a_conv_2/kernel/read 2022-09-20 02:41:30,267 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1a_conv_2/bias/read 2022-09-20 02:41:30,267 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1a_conv_shortcut/kernel/read 2022-09-20 02:41:30,267 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1a_conv_shortcut/bias/read 2022-09-20 02:41:30,267 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1b_conv_1/kernel/read 2022-09-20 02:41:30,268 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1b_conv_1/bias/read 2022-09-20 02:41:30,268 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1b_conv_2/kernel/read 2022-09-20 02:41:30,268 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1b_conv_2/bias/read 2022-09-20 02:41:30,268 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1b_conv_shortcut/kernel/read 2022-09-20 02:41:30,268 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_1b_conv_shortcut/bias/read 2022-09-20 02:41:30,268 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2a_conv_1/kernel/read 2022-09-20 02:41:30,268 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2a_conv_1/bias/read 2022-09-20 02:41:30,269 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2a_conv_2/kernel/read 2022-09-20 02:41:30,269 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2a_conv_2/bias/read 2022-09-20 02:41:30,269 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2a_conv_shortcut/kernel/read 2022-09-20 02:41:30,269 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2a_conv_shortcut/bias/read 2022-09-20 02:41:30,269 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2b_conv_1/kernel/read 2022-09-20 02:41:30,270 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2b_conv_1/bias/read 2022-09-20 02:41:30,270 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2b_conv_2/kernel/read 2022-09-20 02:41:30,270 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2b_conv_2/bias/read 2022-09-20 02:41:30,270 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2b_conv_shortcut/kernel/read 2022-09-20 02:41:30,270 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_2b_conv_shortcut/bias/read 2022-09-20 02:41:30,270 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3a_conv_1/kernel/read 2022-09-20 02:41:30,271 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3a_conv_1/bias/read 2022-09-20 02:41:30,271 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3a_conv_2/kernel/read 2022-09-20 02:41:30,272 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3a_conv_2/bias/read 2022-09-20 02:41:30,272 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3a_conv_shortcut/kernel/read 2022-09-20 02:41:30,273 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3a_conv_shortcut/bias/read 2022-09-20 02:41:30,273 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3b_conv_1/kernel/read 2022-09-20 02:41:30,274 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3b_conv_1/bias/read 2022-09-20 02:41:30,274 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3b_conv_2/kernel/read 2022-09-20 02:41:30,275 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3b_conv_2/bias/read 2022-09-20 02:41:30,275 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3b_conv_shortcut/kernel/read 2022-09-20 02:41:30,276 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_3b_conv_shortcut/bias/read 2022-09-20 02:41:30,276 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4a_conv_1/kernel/read 2022-09-20 02:41:30,278 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4a_conv_1/bias/read 2022-09-20 02:41:30,278 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4a_conv_2/kernel/read 2022-09-20 02:41:30,286 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4a_conv_2/bias/read 2022-09-20 02:41:30,287 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4a_conv_shortcut/kernel/read 2022-09-20 02:41:30,287 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4a_conv_shortcut/bias/read 2022-09-20 02:41:30,287 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4b_conv_1/kernel/read 2022-09-20 02:41:30,295 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4b_conv_1/bias/read 2022-09-20 02:41:30,295 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4b_conv_2/kernel/read 2022-09-20 02:41:30,303 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4b_conv_2/bias/read 2022-09-20 02:41:30,303 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4b_conv_shortcut/kernel/read 2022-09-20 02:41:30,303 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=block_4b_conv_shortcut/bias/read 2022-09-20 02:41:30,304 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_1/kernel/read 2022-09-20 02:41:30,310 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_1/bias/read 2022-09-20 02:41:30,311 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_1/mul 2022-09-20 02:41:30,311 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_1/mul_1 2022-09-20 02:41:30,311 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_1/kernel/read 2022-09-20 02:41:30,313 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_1/bias/read 2022-09-20 02:41:30,313 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_2/kernel/read 2022-09-20 02:41:30,314 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_2/bias/read 2022-09-20 02:41:30,314 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_2/mul 2022-09-20 02:41:30,315 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_2/mul_1 2022-09-20 02:41:30,315 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_2/kernel/read 2022-09-20 02:41:30,315 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_2/bias/read 2022-09-20 02:41:30,315 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_3/kernel/read 2022-09-20 02:41:30,316 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_3/bias/read 2022-09-20 02:41:30,316 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_3/mul 2022-09-20 02:41:30,316 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_3/mul_1 2022-09-20 02:41:30,316 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_3/kernel/read 2022-09-20 02:41:30,317 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_3/bias/read 2022-09-20 02:41:30,317 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_4/kernel/read 2022-09-20 02:41:30,317 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_transpose_4/bias/read 2022-09-20 02:41:30,317 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_4/mul 2022-09-20 02:41:30,317 [INFO] tf2onnx.tfonnx: folding node using tf type=Mul, name=conv2d_transpose_4/mul_1 2022-09-20 02:41:30,317 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_4/kernel/read 2022-09-20 02:41:30,318 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_4/bias/read 2022-09-20 02:41:30,318 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_5/kernel/read 2022-09-20 02:41:30,318 [INFO] tf2onnx.tfonnx: folding node using tf type=Identity, name=conv2d_5/bias/read 2022-09-20 02:41:30,580 [INFO] tf2onnx.optimizer: Optimizing ONNX model 2022-09-20 02:41:31,179 [INFO] tf2onnx.optimizer: After optimization: Cast -4 (4->0), Concat -4 (7->3), Const -66 (134->68), Identity -1 (1->0), Reshape -26 (26->0), Shape -4 (4->0), Slice -4 (4->0), Squeeze -4 (4->0), Unsqueeze -16 (16->0) 2022-09-20 02:41:31,473 [INFO] iva.unet.export.unet_exporter: New input/output 2022-09-20 02:41:31,473 [INFO] iva.unet.export.unet_exporter: [name: "input_1:0" type { tensor_type { elem_type: 1 shape { dim { dim_param: "unk__174" } dim { dim_value: 3 } dim { dim_value: 640 } dim { dim_value: 640 } } } } ] 2022-09-20 02:41:31,473 [INFO] iva.unet.export.unet_exporter: [name: "argmax_1" type { tensor_type { elem_type: 7 shape { dim { dim_param: "N" } dim { dim_value: 640 } dim { dim_value: 640 } dim { dim_value: 1 } } } } ] 2022-09-20 02:41:32,030 [INFO] numba.cuda.cudadrv.driver: init 2022-09-20 02:41:32,192 [INFO] iva.unet.export.unet_exporter: Converted model was saved into /workspace/tao_unet/unet/export_640_640/fp32/model.fp32.etlt 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 0: Train Id 0 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 1: Train Id 1 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 2: Train Id 2 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 3: Train Id 3 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 4: Train Id 4 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 5: Train Id 5 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 6: Train Id 6 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 7: Train Id 7 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 8: Train Id 8 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 9: Train Id 9 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 10: Train Id 10 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 11: Train Id 11 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 12: Train Id 12 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 13: Train Id 13 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 14: Train Id 14 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 15: Train Id 15 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 16: Train Id 16 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 17: Train Id 17 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 18: Train Id 18 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 19: Train Id 19 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 20: Train Id 20 2022-09-20 02:41:32,206 [INFO] iva.unet.model.utilities: Label Id 21: Train Id 21 2022-09-20 02:42:05,181 [INFO] root: Export complete. 2022-09-20 10:42:07,813 [INFO] tlt.components.docker_handler.docker_handler: Stopping container.