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https://github.com/saymrwulf/pytorch.git
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17637f2b03
Summary: * Many op in lstm part of the model don't have implementation in ideep/mkl, and it doesn't make sense to copy back and forth for the few available ops because majority of RNN will be on CPU * Thus the strategy is to enable mkl only for the resnet18 part of the model, then switch to default cpu engine for the lstm part * The net may contain some external_inputs falsely added during ONNX->Caffe2. Canary in service shows their existence could leads to service crash (presumably due to these blob somehow get shared between threads). They're now manually removed which seem to be enough to avoid the crash. Reviewed By: viswanathgs Differential Revision: D8888763 fbshipit-source-id: da7761bcb7d876ff7bbb6640ae4b24712c0b1de6 |
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| .. | ||
| mkl_concat_op_test.py | ||
| mkl_conv_op_test.py | ||
| mkl_copy_op_test.py | ||
| mkl_elementwise_add_op_test.py | ||
| mkl_elementwise_sum_op_test.py | ||
| mkl_fc_op_test.py | ||
| mkl_fc_speed_test.py | ||
| mkl_fill_op_test.py | ||
| mkl_LRN_op_test.py | ||
| mkl_LRN_speed_test.py | ||
| mkl_pool_op_test.py | ||
| mkl_pool_speed_test.py | ||
| mkl_relu_op_test.py | ||
| mkl_sbn_op_test.py | ||
| mkl_sbn_speed_test.py | ||
| mkl_sigmoid_op_test.py | ||
| mkl_speed_test.py | ||
| mkl_squeeze_op_test.py | ||
| rewrite_graph.py | ||
| rewrite_graph_test.py | ||