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tensorflow/c/eager/c_api_test.cc
ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); float product[4] = {0}; EXPECT_EQ(sizeof(product), TF_TensorByteSize(t)); memcpy(&product[0], TF_TensorData(t), TF_TensorByteSize(t)); TF_DeleteTensor(t); EXPECT_EQ(7, product[0]); EXPECT_EQ(10, product[1]); EXPECT_EQ(15, product[2]); EXPECT_EQ(22, product[3]); TF_DeleteStatus(status); }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Aug 03 20:50:20 GMT 2023 - 94.6K bytes - Viewed (1) -
tensorflow/c/eager/c_api_experimental_test.cc
ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); float product[4] = {0}; EXPECT_EQ(sizeof(product), TF_TensorByteSize(t)); memcpy(&product[0], TF_TensorData(t), TF_TensorByteSize(t)); TF_DeleteTensor(t); EXPECT_EQ(7, product[0]); EXPECT_EQ(10, product[1]); EXPECT_EQ(15, product[2]); EXPECT_EQ(22, product[3]); TF_DeleteStatus(status); }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Aug 03 03:14:26 GMT 2023 - 31.5K bytes - Viewed (1) -
tensorflow/c/c_api.cc
} // TF_Graph functions --------------------------------------------------------- TF_Graph::TF_Graph() : graph(tensorflow::OpRegistry::Global()), refiner(graph.versions().producer(), graph.op_registry()), delete_requested(false), parent(nullptr), parent_inputs(nullptr) { // Tell the shape refiner to also run shape inference on functions.
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tensorflow/c/c_api.h
TF_Status* status); // In this code: // TF_Output producer = TF_OperationInput(consumer); // There is an edge from producer.oper's output (given by // producer.index) to consumer.oper's input (given by consumer.index). TF_CAPI_EXPORT extern TF_Output TF_OperationInput(TF_Input oper_in);
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Oct 26 21:08:15 GMT 2023 - 82.3K bytes - Viewed (3) -
tensorflow/c/eager/c_api.h
// This function will block till the operation that produces `h` has completed. TF_CAPI_EXPORT extern int64_t TFE_TensorHandleDim(TFE_TensorHandle* h, int dim_index, TF_Status* status); // Returns the device of the operation that produced `h`. If `h` was produced by
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Apr 27 21:07:00 GMT 2023 - 22.8K bytes - Viewed (1) -
.github/ISSUE_TEMPLATE/tflite-converter-issue.md
``` ### 3. Failure after conversion If the conversion is successful, but the generated model is wrong, then state what is wrong: - Model produces wrong results and/or has lesser accuracy. - Model produces correct results, but it is slower than expected. ### 4. (optional) RNN conversion support If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title.
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tensorflow/c/eager/c_api_experimental.h
TF_Status* status); // Returns the device type of the operation that produced `h`. TF_CAPI_EXPORT extern const char* TFE_TensorHandleDeviceType( TFE_TensorHandle* h, TF_Status* status); // Returns the device ID of the operation that produced `h`. TF_CAPI_EXPORT extern int TFE_TensorHandleDeviceID(TFE_TensorHandle* h,
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Feb 21 22:37:46 GMT 2024 - 39.5K bytes - Viewed (0) -
ci/official/requirements_updater/README.md
``` ## Requirements updater Requirements updater is a standalone tool, intended to simplify process of updating requirements for multiple minor versions of Python. It takes in a file with a set of dependencies, and produces a more detailed requirements file for each version, with hashes specified for each dependency required, as well as their sub-dependencies. ### How to update/add requirements
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tensorflow/c/eager/gradients.h
// // `GetID` returns a unique id for the wrapped tensor which is used to maintain // a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of // the op that produced it (or -1 if this tensor was watched using // `GradientTape::Watch`.) The op_id is simply a unique index assigned to each // op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
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tensorflow/c/eager/c_api_remote_test_util.cc
TFE_DeleteTensorHandle(retval_task0); float product[4] = {0}; EXPECT_EQ(sizeof(product), TF_TensorByteSize(t)); memcpy(&product[0], TF_TensorData(t), TF_TensorByteSize(t)); TF_DeleteTensor(t); EXPECT_EQ(7, product[0]); EXPECT_EQ(10, product[1]); EXPECT_EQ(15, product[2]); EXPECT_EQ(22, product[3]); TFE_DeleteTensorHandle(h0_task0); TFE_DeleteTensorHandle(h1_task0);
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