function.Defun( shape_func=lambda op: [[1] + op.inputs[0].get_shape().as_list()])

parameterized.parameters( # Rename parameter: delimiter -> sep and add .to_sparse() ["tf.string_sp

function.Defun(*input_dtypes)

function.Defun( dtypes.float32, shape_func=lambda op: [op.inputs[0].get_shape()])

keras_export('keras.layers.Input', 'keras.Input')

deprecated("2018-08-20", "Use tf.print instead of tf.Print. Note that " "tf.print returns a no-out

function.Defun( *func.declared_input_types, func_name="%s_Wrapper" % func.name)

ops.RegisterGradient("Conv2DBackpropInput")

ops.RegisterGradient("Conv3DBackpropInputV2")

ops.RegisterGradient("DepthwiseConv2dNativeBackpropInput")

ops.RegisterGradient("ExtractImagePatches")

ops.RegisterGradient("ExtractVolumePatches")

ops.RegisterGradient("OptionalGetValue")

ops.RegisterGradient("TensorListGetItem")

ops.RegisterGradient("XlaClusterOutput")

def_function.function( input_signature=[tensor_spec.TensorSpec(None, dtypes.float32)])

def_function.function(input_signature=[])

tf.function(input_signature=[tf.TensorSpec([None], tf.dtypes.string)])

deprecation.deprecated( None, "Use `tf.data.experimental.CheckpointInputPipelineHook(...)`.")

deprecated(None, 'Please feed input to tf.data to support dask.')

deprecation.deprecated( None, "Queue-based input pipelines have been replaced by `tf.data`. Use "

deprecated(None, "Use tf.initializers.variance_scaling instead with distribution="

dispatch.dispatch_for_types(linalg.adjoint, LinearOperator)

dispatch.dispatch_for_types(linalg.cholesky, LinearOperator)

_control_inputs.setter

ops.RegisterStatistics("Conv2DBackpropInput", "flops")

RegisterPForWithArgs("Conv2DBackpropInput", flatten_dims=[2], shape_dim=0)

def_function.function(input_signature=[], autograph=False)

def_function.function(input_signature=[tensor_spec.TensorSpec( shape=None, dtype=dtypes.float32)])

def_function.function(input_signature=[], autograph=False)

dispatch.dispatch_for_types(linalg.det, LinearOperator)

dispatch.dispatch_for_types(linalg.diag_part, LinearOperator)

function.defun( input_signature=[tensor_spec.TensorSpec([], dtypes.string)], autograph=False)

function.defun(input_signature=[tensor_spec.TensorSpec([], dtypes.string)])

function.Defun(dtype, dtype, dtype, func_name='ScaledSoftplusHelper_%s' % dtype.name,

function.Defun(dtype, dtype, dtype, dtype, func_name='ScaledSoftplusHelper_clip_%s' % dt

deprecated( '2016-09-23', 'The signature of the input_fn accepted by export is changing to be '

def_function.function(input_signature=[], autograph=False)

_input_types.setter

_inputs.setter

dispatch.dispatch_for_types(linalg.inv, LinearOperator)

dispatch.dispatch_for_types(linalg.logdet, LinearOperator)

dispatch.dispatch_for_types(math_ops.matmul, LinearOperator)

function.defun( input_signature=[tensor_spec.TensorSpec([], dtypes.string)], autograph=False)

function.defun(input_signature=[tensor_spec.TensorSpec([], dtypes.string)])

function.defun( input_signature=[tensor_spec.TensorSpec([], dtypes.string)], autograph=False)

function.defun(input_signature=[tensor_spec.TensorSpec([], dtypes.string)])

function.defun_with_attributes( input_signature=[tensor_spec.TensorSpec([], dtypes.string)], a

function.defun_with_attributes( input_signature=[tensor_spec.TensorSpec([], dtypes.string)], a

dispatch.dispatch_for_types(linalg.solve, LinearOperator)

dispatch.dispatch_for_types(linalg.trace, LinearOperator)

def_function.function( input_signature=(tensor_spec.TensorSpec(shape=(), dtype=dtypes.string),), a

def_function.function( input_signature=(tensor_spec.TensorSpec(shape=(), dtype=dtypes.string),), a

def_function.function(input_signature=input_signature, autograph=False)

dispatch.add_dispatch_support

def_function.function(input_signature=[ tensor_spec.TensorSpec(shape=None, dtype=dtypes.float32)])

def_function.function(input_signature=[tensor_spec.TensorSpec( shape=None, dtype=dtypes.float32)])

dispatch.add_dispatch_support

deprecation.deprecated_args(None, '`inputs` is now automatically inferred', 'in

dispatch.add_dispatch_support

dispatch.add_dispatch_support

function.defun(input_signature=[{ 'a': tensor_spec.TensorSpec((2, None), dtypes.float32), 'b':

deprecation.deprecated( None, "Queue-based input pipelines have been replaced by `tf.data`. Use " "`tf

dispatch.add_dispatch_support

keras_export('keras.backend.batch_get_value')

deprecation.deprecated( None, "Queue-based input pipelines have been replaced by `tf.data`. Use " "`tf

dispatch.add_dispatch_support

deprecated(None, 'Please use ' 'tf.estimator.export.build_raw_serving_input_receiver_fn.')

deprecated(None, 'Please use ' 'tf.estimator.export.build_parsing_serving_input_receiver_fn.')

def_function.function( input_signature=(tensor_spec.TensorSpec([None, 2], dtypes.float32),

def_function.function( input_signature=(tensor_spec.TensorSpec([None, 2], dtypes.float32),

def_function.function( input_signature=[[tensor_spec.TensorSpec([None, 5], dtypes.float32),

function.defun( input_signature=[tensor_spec.TensorSpec([None, None], dtypes.float32)])

dispatch.add_dispatch_support

deprecated('2017-03-25', 'signature_fns are deprecated. For canned Estimators they are no '

deprecated('2017-03-25', 'signature_fns are deprecated. For canned Estimators they are no '

dispatch.add_dispatch_support

dispatch.add_dispatch_support

def_function.function( input_signature=[tensor_spec.TensorSpec(None, dtypes.float32)])

tf_export('nn.compute_accidental_hits')

tf_export("nn.compute_average_loss")

tf_export(v1=["test.compute_gradient"])

tf_export("test.compute_gradient", v1=[])

tf_export(v1=["test.compute_gradient_error"])

deprecated("2016-12-30", "Use tf.losses.compute_weighted_loss instead.")

tf_export(v1=["losses.compute_weighted_loss"])

dispatch.add_dispatch_support

rev_block_lib.recompute_grad

dispatch.add_dispatch_support

tf_export("get_static_value")

tf_export(v1=["nn.conv2d_backprop_input"])

deprecated_args(None, "Shapes are always computed; don't use the compute_shapes "

deprecation.deprecated( date=None, instructions="Use `tf.get_variable` with a partitioner set.")

dispatch.dispatch_for_types(gen_math_ops.add, CustomTensor)

deprecation.deprecated_args(None, "bytes is deprecated, use input_bytes instead",

decorated_target.setter

function.defun(input_signature=[tensor_spec.TensorSpec([5], dtypes.int64)])

function.defun(input_signature=[tensor_spec.TensorSpec([], dtypes.int32)])

tf_export(v1=["gfile.DeleteRecursively"])

tf_export(v1=["delete_session_tensor"])