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tensorflow/c/experimental/gradients/grad_test_helper.h
void CompareNumericalAndAutodiffGradients( Model model, Model grad_model, AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, bool use_function, double abs_error = 1e-2); void CheckTensorValue(AbstractTensorHandle* t, absl::Span<const float> manuals, absl::Span<const int64_t> dims, double abs_error = 1e-2); Model BuildGradModel(Model forward, GradientRegistry registry);
C - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Thu Jan 14 20:36:51 GMT 2021 - 1.5K bytes - Viewed (0) -
tensorflow/c/eager/unified_api_testutil.h
// outputs = tf.function(model)(inputs) // else: // outputs = model(inputs) Status RunModel(Model model, AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs, bool use_function); Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx); // Return a tensor handle with given type, values and dimensions.
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 4K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.h
#include "tensorflow/c/eager/unified_api_testutil.h" namespace tensorflow { namespace gradients { /* Returns numerical grad inside `dtheta_approx` given `forward` model and * parameter specified by `input_index`. * * I.e. if y = <output of the forward model> and w = inputs[input_index], * this will calculate dy/dw numerically. * * `use_function` indicates whether to use graph mode(true) or eager(false). *
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Dec 11 02:34:32 GMT 2020 - 1.8K bytes - Viewed (0)