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RELEASE.md
replaced with an alternative API in `tf.contrib.seq2seq`. * Intel MKL Integration (https://software.intel.com/en-us/articles/tensorflow-optimizations-on-modern-intel-architecture). Intel developed a number of optimized deep learning primitives: In addition to matrix multiplication and convolution, these building blocks include:
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Mon Apr 29 19:17:57 GMT 2024 - 727.7K bytes - Viewed (8) -
tensorflow/c/c_api_experimental.cc
status->status = tensorflow::errors::NotFound( op_name, " does not have number_attr() defined."); return nullptr; } // The returned string is owned by OpRegistry, so liveness is not a concern. return input_arg.number_attr().c_str(); } int TF_OpIsStateful(const char* op_type, TF_Status* status) { const tensorflow::OpRegistrationData* op_reg_data; status->status =
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 29.4K bytes - Viewed (0) -
configure.py
elif is_windows(): default_cc_opt_flags = '/arch:AVX' else: # On all other platforms, no longer use `-march=native` as this can result # in instructions that are too modern being generated. Users that want # maximum performance should compile TF in their environment and can pass # `-march=native` there. # See https://github.com/tensorflow/tensorflow/issues/45744 and duplicates
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (1)