I use the current setup:
Hardware:
- i7 based Acer system
- NVIDIA GEFORCE RTX
- NVIDIA Jetson Xavier (target)
Software:
- Ubuntu 18.04
- TensorRT v7.2.2
- CUDA Version 10.2.89
- cuDNN v8.1.1
- GNU make >= v4.1
- cmake >= v3.13
- Python 3.6.5
- Uff 0.6.9
- graphsurgeon
Attempt 1
I followed the steps given in sampleUffMaskRCNN README and went on modifying the conv2d_transpose function in /usr/lib/python3.6/dist-packages/uff/converters/tensorflow/converter_functions.py. I also applied the 0001-Update-the-Mask_RCNN-model-from-NHWC-to-NCHW.patch patch.
For test, I used the same sample model provided in the instructions. In short, I replicated all the steps.
The config.py and model.py I used, have been attached below config.py (9.2 KB) model.py (124.6 KB)
I get the error ending with:
Converting to UFF graph
Traceback (most recent call last):
File "mrcnn_to_trt_single.py", line 164, in <module>
main()
File "mrcnn_to_trt_single.py", line 123, in main
text=True, list_nodes=list_nodes)
File "mrcnn_to_trt_single.py", line 157, in convert_model
debug_mode = False
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/uff/converters/tensorflow/conversion_helpers.py", line 276, in from_tensorflow_frozen_model
return from_tensorflow(graphdef, output_nodes, preprocessor, **kwargs)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/uff/converters/tensorflow/conversion_helpers.py", line 225, in from_tensorflow
debug_mode=debug_mode)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/uff/converters/tensorflow/converter.py", line 141, in convert_tf2uff_graph
uff_graph, input_replacements, debug_mode=debug_mode)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/uff/converters/tensorflow/converter.py", line 126, in convert_tf2uff_node
op, name, tf_node, inputs, uff_graph, tf_nodes=tf_nodes, debug_mode=debug_mode)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/uff/converters/tensorflow/converter.py", line 94, in convert_layer
return cls.registry_[op](name, tf_node, inputs, uff_graph, **kwargs)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/uff/converters/tensorflow/converter_functions.py", line 87, in convert_add
uff_graph.binary(inputs[0], inputs[1], 'add', name)
IndexError: list index out of range
The entire logs are here:log1.txt (92.7 KB)
On running the same script but with my model (also based on ResNet101 like the sample model), I get the error ending with:
Traceback (most recent call last):
File "mrcnn_to_trt_single.py", line 164, in <module>
main()
File "mrcnn_to_trt_single.py", line 115, in main
model.load_weights(model_weights_path, by_name=True)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/keras/engine/topology.py", line 2643, in load_weights
f, self.layers, skip_mismatch=skip_mismatch)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/keras/engine/topology.py", line 3248, in load_weights_from_hdf5_group_by_name
K.batch_set_value(weight_value_tuples)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 2365, in batch_set_value
assign_op = x.assign(assign_placeholder)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/ops/variables.py", line 2067, in assign
self._variable, value, use_locking=use_locking, name=name)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/ops/state_ops.py", line 227, in assign
validate_shape=validate_shape)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_state_ops.py", line 66, in assign
use_locking=use_locking, name=name)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/framework/op_def_library.py", line 794, in _apply_op_helper
op_def=op_def)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3357, in create_op
attrs, op_def, compute_device)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 3426, in _create_op_internal
op_def=op_def)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 1770, in __init__
control_input_ops)
File "/home/hotify/trt_sample_try/trt_sample/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 1610, in _create_c_op
raise ValueError(str(e))
ValueError: Dimension 1 in both shapes must be equal, but are 324 and 16. Shapes are [1024,324] and [1024,16]. for 'Assign_682' (op: 'Assign') with input shapes: [1024,324], [1024,16].
The entire logs are: log3.txt (10.1 KB) .
Both models are ResNet101 and still leading to errors. I tried following the post: converting mask rcnn to tensor rt - #31 by ChrisDing but their configuration file is way different from mine. On using theirs, I get the same error.
Any help is appreciated 🙂
