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Results 1 - 7 of 7 for TestTensorHandleWithDims (0.23 sec)
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tensorflow/c/experimental/gradients/nn_grad_test.cc
float X_vals[] = {1.0f, 2.0f, 3.0f, -5.0f, -4.0f, -3.0f, 2.0f, 10.0f, -1.0f}; int64_t X_dims[] = {3, 3}; AbstractTensorHandlePtr X; { AbstractTensorHandle* X_raw; status_ = TestTensorHandleWithDims<float, TF_FLOAT>( immediate_execution_ctx_.get(), X_vals, X_dims, 2, &X_raw); ASSERT_EQ(errors::OK, status_.code()) << status_.message(); X.reset(X_raw); }
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 8.3K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/math_grad_test.cc
GTEST_SKIP(); float A_vals[] = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f}; int64_t A_dims[] = {3, 3}; AbstractTensorHandlePtr A; { AbstractTensorHandle* A_raw; status_ = TestTensorHandleWithDims<float, TF_FLOAT>( immediate_execution_ctx_.get(), A_vals, A_dims, 2, &A_raw); ASSERT_EQ(errors::OK, status_.code()) << status_.message(); A.reset(A_raw); }
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Thu Apr 13 17:32:14 GMT 2023 - 16.3K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.cc
{ vector<int32_t> vals(num_dims_out); int64_t vals_shape[] = {num_dims_out}; Range(&vals, 0, num_dims_out); AbstractTensorHandle* sum_dims_raw = nullptr; TF_RETURN_IF_ERROR(TestTensorHandleWithDims<int32_t, TF_INT32>( ctx, vals.data(), vals_shape, 1, &sum_dims_raw)); sum_dims.reset(sum_dims_raw); } // Reduce sum the output on all dimensions.
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7.3K bytes - Viewed (0) -
tensorflow/c/eager/unified_api_testutil.h
Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx); // Return a tensor handle with given type, values and dimensions. template <class T, TF_DataType datatype> Status TestTensorHandleWithDims(AbstractContext* ctx, const T* data, const int64_t* dims, int num_dims, AbstractTensorHandle** tensor) {
C - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 4K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker_test.cc
TEST_P(GradientCheckerTest, TestMatMul) { float A_vals[] = {1.0f, 2.0f, 3.0f, 4.0f}; int64_t A_dims[] = {2, 2}; AbstractTensorHandlePtr A; { AbstractTensorHandle* A_raw; Status s = TestTensorHandleWithDims<float, TF_FLOAT>(ctx_.get(), A_vals, A_dims, 2, &A_raw); ASSERT_EQ(errors::OK, s.code()) << s.message(); A.reset(A_raw); }
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Fri Apr 14 10:03:59 GMT 2023 - 6.5K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test_util.h
int64_t dims[], int num_dims); // Return a tensor handle with given type, values and dimensions. template <class T, TF_DataType datatype> TFE_TensorHandle* TestTensorHandleWithDims(TFE_Context* ctx, const T* data, const int64_t* dims, int num_dims) { TF_Status* status = TF_NewStatus();
C - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Mon Jul 17 23:43:59 GMT 2023 - 7.7K bytes - Viewed (0) -
tensorflow/c/eager/unified_api_test.cc
} AbstractTensorHandlePtr x; { AbstractTensorHandle* x_raw = nullptr; float data[] = {0., 0., 0., 0., 0., 0., 0., 0}; int64_t dim_sizes[] = {2, 4}; Status s = TestTensorHandleWithDims<float, TF_FLOAT>(ctx.get(), data, dim_sizes, 2, &x_raw); ASSERT_EQ(errors::OK, s.code()) << s.message(); x.reset(x_raw); }
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 6.7K bytes - Viewed (0)