AI-TensorFlow-Libtensorflow

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lib/AI/TensorFlow/Libtensorflow/DeviceList.pm  view on Meta::CPAN

	Incarnation => 'uint64_t',
);
for my $method (keys %methods) {
	$ffi->attach( [ "DeviceList${method}" => $method ] => [
		arg TF_DeviceList => 'list',
		arg int => 'index',
		arg TF_Status => 'status'
	] => $methods{$method} );
}

### From tensorflow/core/framework/types.cc
my %DEVICE_TYPES = (
	DEFAULT => "DEFAULT",
	CPU => "CPU",
	GPU => "GPU",
	TPU => "TPU",
	TPU_SYSTEM => "TPU_SYSTEM",
);

1;

lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

  If `func` or `grad` are already in `g`, TF_GraphCopyFunction has no
  effect on them, but can establish the function->gradient relationship
  between them if `func` does not already have a gradient. If `func` already
  has a gradient different from `grad`, an error is returned.
  
  `func` must not be null.
  If `grad` is null and `func` is not in `g`, `func` is added without a
  gradient.
  If `grad` is null and `func` is in `g`, TF_GraphCopyFunction is a noop.
  `grad` must have appropriate signature as described in the doc of
  GradientDef in tensorflow/core/framework/function.proto.
  
  If successful, status is set to OK and `func` and `grad` are added to `g`.
  Otherwise, status is set to the encountered error and `g` is unmodified.

=back

  /* From <tensorflow/c/c_api.h> */
  TF_CAPI_EXPORT extern void TF_GraphCopyFunction(TF_Graph* g,
                                                  const TF_Function* func,
                                                  const TF_Function* grad,

lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

=head2 TF_NewApiDefMap

=over 2

  Creates a new TF_ApiDefMap instance.
  
  Params:
   op_list_buffer - TF_Buffer instance containing serialized OpList
     protocol buffer. (See
     https://www.tensorflow.org/code/tensorflow/core/framework/op_def.proto
     for the OpList proto definition).
   status - Set to OK on success and an appropriate error on failure.

=back

  /* From <tensorflow/c/c_api.h> */
  TF_CAPI_EXPORT extern TF_ApiDefMap* TF_NewApiDefMap(TF_Buffer* op_list_buffer,
                                                      TF_Status* status);

=head2 TF_DeleteApiDefMap

lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

  /* From <tensorflow/c/c_api.h> */
  TF_CAPI_EXPORT extern void TF_DeleteApiDefMap(TF_ApiDefMap* apimap);

=head2 TF_ApiDefMapPut

=over 2

  Add ApiDefs to the map.
  
  `text` corresponds to a text representation of an ApiDefs protocol message.
  (https://www.tensorflow.org/code/tensorflow/core/framework/api_def.proto).
  
  The provided ApiDefs will be merged with existing ones in the map, with
  precedence given to the newly added version in case of conflicts with
  previous calls to TF_ApiDefMapPut.

=back

  /* From <tensorflow/c/c_api.h> */
  TF_CAPI_EXPORT extern void TF_ApiDefMapPut(TF_ApiDefMap* api_def_map,
                                             const char* text, size_t text_len,

lib/AI/TensorFlow/Libtensorflow/Manual/CAPI.pod  view on Meta::CPAN

=back

  /* From <tensorflow/c/kernels.h> */
  TF_CAPI_EXPORT extern TF_Buffer* TF_OpKernelConstruction_GetNodeDef(
      TF_OpKernelConstruction* ctx, TF_Status* status);

=head2 TF_GetFrameId

=over 2

  Returns the frame ID of the given context.

=back

  /* From <tensorflow/c/kernels.h> */
  TF_CAPI_EXPORT extern uint64_t TF_GetFrameId(TF_OpKernelContext* ctx);

=head2 TF_GetIterId

=over 2