Skip to content
Permalink
Branch: master
Find file Copy path
1 contributor

Users who have contributed to this file

594 lines (535 sloc) 32.6 KB

TensorFlow Namespaces

Status Accepted
Author(s) Anna Revinskaya (annarev@google.com), Andrew Selle (aselle@google.com)
Sponsor Martin Wicke (wicke@google.com)
Updated 2018-08-27

Objective

This document proposes organizing TensorFlow API symbols in corresponding logical subnamespaces. As TensorFlow library grows, it is important to structure namespaces in a clear way for easier discoverability and usability.

We define endpoint as full name that can be used to access a TensorFlow symbol. For e.g. name_scope can be accessed using either tf.name_scope or tf.keras.backend.name_scope. Therefore, name_scope has 2 endpoints: tf.name_scope and tf.keras.backend.name_scope.

At a high level we have the following goals:

  • Add a few additional namespaces.
  • Add additional endpoints for TensorFlow symbols in relevant namespaces.
  • Remove some of the existing endpoints.

Motivation

TensorFlow currently has over 2000 endpoints total including over 500 endpoints in the root namespace. As number of symbols grows, it is important to maintain a clear structure to aid discoverability.

Certain API symbol placements could be improved:

  • Some namespaces were created recently and might not contain all the corresponding symbols. For e.g. tf.math namespace was added recently. Symbols such as tf.round are not in tf.math namespace even though logically they belong in that namespace.
  • Some symbols are included in the root namespace even though they are rarely used (for e.g. tf.zeta).
  • Some symbols currently start with a prefix that could really be replaced by introducing a subnamespace (for e.g. tf.string_strip vs tf.strings.strip, tf.sparse_maximum vs tf.sparse.maximum).
  • Certain deep hierarchies seem redundant and could be flattened (for e.g. tf.saved_model.signature_constants.CLASSIFY_INPUTS could be moved to tf.saved_model.CLASSIFY_INPUTS).
  • To keep clear structure and reduce duplication, we want to collect all layers, losses and metrics under the tf.keras namespace.

In general, we want to balance flatness and browsability. Flat hierarchies allow for shorter endpoint names that are easy to remember (for e.g. tf.add vs tf.math.add). At the same time subnamespaces support easier browsability (for e.g. tf.math namespace would contain all math functions making it easier to discover available symbols).

Furthermore, TensorFlow API has many users. Therefore, we should avoid removing endpoints if they are frequently used.

Design Proposal

Additional namespaces

We plan to add the following additional namespaces:

tf.random - will contain random sampling ops. tf.keras.layers - will contain all symbols that are currently under tf.layers. Note that signatures of these symbols will likely change to match layers under tf.keras.layers better. tf.keras.losses - will contain all symbols that are currently under tf.losses. Note that signatures of these symbols will likely change to match losses under tf.keras.losses better. tf.keras.metrics - will contain all symbols that are currently under tf.metrics. Note that signatures of these symbols will likely change to match metrics under tf.keras.metrics better.

Note that we already introduced some new namespaces earlier in June, specifically

tf.debugging - ops helpful for debugging, such as asserts. We also want to move TensorFlow Debugger to tf.debugging namespace.

tf.dtypes - data types.

tf.io - ops for reading and writing.

tf.quantization - ops related to quantization.

Deprecated namespaces

We plan to deprecate entire contents of the following namespaces:

tf.logging - Python logging module can be used instead. tf.manip - We will keep endpoints in root for symbols in tf.manip. tf.manip was added recently but most tensor manipulation ops are frequently used and it makes sense to keep them in root instead.

Additional endpoints

We will add new endpoints for existing symbols to make sure each namespace contains all relevant endpoints.

See list of endpoints we want to add in Appendix 1: Additional Endpoints. Note: the list in the appendix does not include new endpoints for symbols under tf.layers, tf.losses and tf.metrics namespaces since all symbols under these namespaces will have new endpoints added under tf.keras.layers, tf.keras.losses and tf.keras.metrics respectively. So, we don't need to list these endpoint changes individually.

Deprecated endpoints

We also want to remove some of the existing endpoints. Specifically we were looking for endpoints to remove based on the following criteria:

  • Remove endpoints if they have preferred replacement and if these endpoints are not frequently used.
  • Remove all endpoints that have been moved to tf.quantization namespace.
  • Remove all endpoints that have been moved to tf.random namespace.
  • Remove all endpoints from tf.logging.

In total, we propose to remove 214 endpoints, including 171 endpoints in the root namespace.

See the list of endpoints we want to remove in Appendix 2: Deprecated Endpoints. Note: the list in the appendix does not include endpoints under tf.logging since entire contents of this module will be deprecated. So, we don't need to list these endpoints individually.

Impact

Browsing for symbols should become easier. For e.g. page for tf.math namespace should display all math functions that TensorFlow provides. Similarly, tf.sets namespace page should display all available set operations.

Removing symbol endpoints would break references in user code. We plan to apply removals as a part of TensorFlow 2.0 release and provide a conversion script that would replace deprecated references with canonical ones. Initial script is at https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/compatibility/tf_upgrade_v2.py. It will be updated to match changes in this doc.

Work Estimates

Work will be done in multiple stages:

  1. We will first add new endpoints. I have some changes ready, so this step should take 1-2 weeks.
  2. Second step is to remove deprecated endpoints. This will be done later as a part of TensorFlow 2.0 release. Removing endpoints will take about 2 weeks.

Appendix 1: Additional Endpoints

In addition to symbols in this table, we plan to add all symbols under tf.layers, tf.losses, tf.metrics to tf.keras.layers, tf.keras.losses, tf.keras.metrics respectively.

Current name New names
tf.Assert tf.debugging.Assert
tf.COMPILER_VERSION tf.version.COMPILER_VERSION
tf.CXX11_ABI_FLAG tf.sysconfig.CXX11_ABI_FLAG
tf.DType tf.dtypes.DType
tf.FixedLenFeature tf.io.FixedLenFeature
tf.FixedLenSequenceFeature tf.io.FixedLenSequenceFeature
tf.GIT_VERSION tf.version.GIT_VERSION
tf.GRAPH_DEF_VERSION tf.version.GRAPH_DEF_VERSION
tf.GRAPH_DEF_VERSION_MIN_CONSUMER tf.version.GRAPH_DEF_VERSION_MIN_CONSUMER
tf.GRAPH_DEF_VERSION_MIN_PRODUCER tf.version.GRAPH_DEF_VERSION_MIN_PRODUCER
tf.HistogramProto tf.summary.HistogramProto
tf.MONOLITHIC_BUILD tf.sysconfig.MONOLITHIC_BUILD
tf.PaddingFIFOQueue tf.io.PaddingFIFOQueue
tf.Print tf.debugging.Print
tf.PriorityQueue tf.io.PriorityQueue
tf.QUANTIZED_DTYPES tf.dtypes.QUANTIZED_DTYPES
tf.QueueBase tf.io.QueueBase
tf.RandomShuffleQueue tf.io.RandomShuffleQueue
tf.SparseConditionalAccumulator tf.sparse.SparseConditionalAccumulator
tf.SparseFeature tf.io.SparseFeature
tf.SparseTensor tf.sparse.SparseTensor
tf.SparseTensorValue tf.sparse.SparseTensorValue
tf.SummaryMetadata tf.summary.SummaryMetadata
tf.VERSION tf.version.VERSION
tf.VarLenFeature tf.io.VarLenFeature
tf.abs tf.math.abs
tf.accumulate_n tf.math.accumulate_n
tf.add_n tf.math.add_n
tf.angle tf.math.angle
tf.argmax tf.math.argmax
tf.argmin tf.math.argmin
tf.as_dtype tf.dtypes.as_dtype
tf.assert_equal tf.debugging.assert_equal
tf.assert_greater tf.debugging.assert_greater
tf.assert_greater_equal tf.debugging.assert_greater_equal
tf.assert_integer tf.debugging.assert_integer
tf.assert_less tf.debugging.assert_less
tf.assert_less_equal tf.debugging.assert_less_equal
tf.assert_near tf.debugging.assert_near
tf.assert_negative tf.debugging.assert_negative
tf.assert_non_negative tf.debugging.assert_non_negative
tf.assert_non_positive tf.debugging.assert_non_positive
tf.assert_none_equal tf.debugging.assert_none_equal
tf.assert_positive tf.debugging.assert_positive
tf.assert_proper_iterable tf.debugging.assert_proper_iterable
tf.assert_rank tf.debugging.assert_rank
tf.assert_rank_at_least tf.debugging.assert_rank_at_least
tf.assert_rank_in tf.debugging.assert_rank_in
tf.assert_same_float_dtype tf.debugging.assert_same_float_dtype
tf.assert_scalar tf.debugging.assert_scalar
tf.assert_type tf.debugging.assert_type
tf.bfloat16 tf.dtypes.bfloat16
tf.bitcast tf.dtypes.bitcast
tf.bincount tf.math.bincount
tf.bool tf.dtypes.bool
tf.cast tf.dtypes.cast
tf.complex tf.dtypes.complex
tf.complex128 tf.dtypes.complex128
tf.complex64 tf.dtypes.complex64
tf.confusion_matrix tf.train.confusion_matrix
tf.conj tf.math.conj
tf.count_nonzero tf.math.count_nonzero
tf.cumprod tf.math.cumprod
tf.cumsum tf.math.cumsum
tf.decode_csv tf.io.decode_csv
tf.depth_to_space tf.nn.depth_to_space
tf.deserialize_many_sparse tf.io.deserialize_many_sparse
tf.divide tf.math.divide
tf.double tf.dtypes.double
tf.erf tf.math.erf
tf.float16 tf.dtypes.float16
tf.float32 tf.dtypes.float32
tf.float64 tf.dtypes.float64
tf.floordiv tf.math.floordiv
tf.floormod tf.math.floormod
tf.get_seed tf.random.get_seed
tf.global_norm tf.linalg.global_norm
tf.half tf.dtypes.half
tf.imag tf.math.imag
tf.import_graph_def tf.graph_util.import_graph_def
tf.int16 tf.dtypes.int16
tf.int32 tf.dtypes.int32
tf.int64 tf.dtypes.int64
tf.int8 tf.dtypes.int8
tf.is_non_decreasing tf.debugging.is_non_decreasing
tf.is_numeric_tensor tf.debugging.is_numeric_tensor
tf.is_strictly_increasing tf.debugging.is_strictly_increasing
tf.lbeta tf.math.lbeta
tf.log_sigmoid tf.math.log_sigmoid
tf.logical_xor tf.math.logical_xor
tf.manip.roll tf.roll
tf.matmul tf.linalg.matmul
tf.mod tf.math.mod
tf.multinomial tf.random.multinomial
tf.multiply tf.math.multiply
tf.negative tf.math.negative
tf.nn.in_top_k tf.math.in_top_k
tf.nn.l2_normalize tf.math.l2_normalize, tf.linalg.l2_normalize
tf.nn.log_softmax tf.math.log_softmax
tf.nn.log_uniform_candidate_sampler tf.random.log_uniform_candidate_sampler
tf.nn.sigmoid tf.math.sigmoid
tf.nn.softmax tf.math.softmax
tf.nn.top_k tf.math.top_k
tf.nn.uniform_candidate_sampler tf.random.uniform_candidate_sampler
tf.nn.zero_fraction tf.math.zero_fraction
tf.parse_example tf.io.parse_example
tf.parse_single_example tf.io.parse_single_example
tf.parse_single_sequence_example tf.io.parse_single_sequence_example
tf.pow tf.math.pow
tf.python_io.TFRecordCompressionType tf.io.TFRecordCompressionType
tf.python_io.TFRecordOptions tf.io.TFRecordOptions
tf.python_io.TFRecordWriter tf.io.TFRecordWriter
tf.python_io.tf_record_iterator tf.io.tf_record_iterator
tf.qint16 tf.dtypes.qint16
tf.qint32 tf.dtypes.qint32
tf.qint8 tf.dtypes.qint8
tf.quantize tf.quantization.quantize
tf.quantize_v2 tf.quantization.quantize_v2
tf.quint16 tf.dtypes.quint16
tf.quint8 tf.dtypes.quint8
tf.random_crop tf.image.random_crop
tf.random_gamma tf.random.gamma
tf.random_normal tf.random.normal
tf.random_poisson tf.random.poisson
tf.random_shuffle tf.random.shuffle
tf.random_uniform tf.random.uniform
tf.real tf.math.real
tf.realdiv tf.math.realdiv
tf.reduce_all tf.math.reduce_all
tf.reduce_any tf.math.reduce_any
tf.reduce_join tf.math.reduce_join
tf.reduce_logsumexp tf.math.reduce_logsumexp
tf.reduce_max tf.math.reduce_max
tf.reduce_mean tf.math.reduce_mean
tf.reduce_min tf.math.reduce_min
tf.reduce_prod tf.math.reduce_prod
tf.reduce_sum tf.math.reduce_sum
tf.round tf.math.round
tf.saturate_cast tf.dtypes.saturate_cast
tf.saved_model.builder.SavedModelBuilder tf.saved_model.SavedModelBuilder
tf.saved_model.constants.ASSETS_DIRECTORY tf.saved_model.ASSETS_DIRECTORY
tf.saved_model.constants.ASSETS_KEY tf.saved_model.ASSETS_KEY
tf.saved_model.constants.LEGACY_INIT_OP_KEY tf.saved_model.LEGACY_INIT_OP_KEY
tf.saved_model.constants.MAIN_OP_KEY tf.saved_model.MAIN_OP_KEY
tf.saved_model.constants.SAVED_MODEL_FILENAME_PB tf.saved_model.SAVED_MODEL_FILENAME_PB
tf.saved_model.constants.SAVED_MODEL_FILENAME_PBTXT tf.saved_model.SAVED_MODEL_FILENAME_PBTXT
tf.saved_model.constants.SAVED_MODEL_SCHEMA_VERSION tf.saved_model.SAVED_MODEL_SCHEMA_VERSION
tf.saved_model.constants.VARIABLES_DIRECTORY tf.saved_model.VARIABLES_DIRECTORY
tf.saved_model.constants.VARIABLES_FILENAME tf.saved_model.VARIABLES_FILENAME
tf.saved_model.loader.load tf.saved_model.load
tf.saved_model.loader.maybe_saved_model_directory tf.saved_model.maybe_saved_model_directory
tf.saved_model.main_op.main_op_with_restore tf.saved_model.main_op_with_restore
tf.saved_model.signature_constants.CLASSIFY_INPUTS tf.saved_model.CLASSIFY_INPUTS
tf.saved_model.signature_constants.CLASSIFY_METHOD_NAME tf.saved_model.CLASSIFY_METHOD_NAME
tf.saved_model.signature_constants.CLASSIFY_OUTPUT_CLASSES tf.saved_model.CLASSIFY_OUTPUT_CLASSES
tf.saved_model.signature_constants.CLASSIFY_OUTPUT_SCORES tf.saved_model.CLASSIFY_OUTPUT_SCORES
tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY
tf.saved_model.signature_constants.PREDICT_INPUTS tf.saved_model.PREDICT_INPUTS
tf.saved_model.signature_constants.PREDICT_METHOD_NAME tf.saved_model.PREDICT_METHOD_NAME
tf.saved_model.signature_constants.PREDICT_OUTPUTS tf.saved_model.PREDICT_OUTPUTS
tf.saved_model.signature_constants.REGRESS_INPUTS tf.saved_model.REGRESS_INPUTS
tf.saved_model.signature_constants.REGRESS_METHOD_NAME tf.saved_model.REGRESS_METHOD_NAME
tf.saved_model.signature_constants.REGRESS_OUTPUTS tf.saved_model.REGRESS_OUTPUTS
tf.saved_model.signature_def_utils.build_signature_def tf.saved_model.build_signature_def
tf.saved_model.signature_def_utils.classification_signature_def tf.saved_model.classification_signature_def
tf.saved_model.signature_def_utils.is_valid_signature tf.saved_model.is_valid_signature
tf.saved_model.signature_def_utils.predict_signature_def tf.saved_model.predict_signature_def
tf.saved_model.signature_def_utils.regression_signature_def tf.saved_model.regression_signature_def
tf.saved_model.tag_constants.GPU tf.saved_model.GPU
tf.saved_model.tag_constants.SERVING tf.saved_model.SERVING
tf.saved_model.tag_constants.TPU tf.saved_model.TPU
tf.saved_model.tag_constants.TRAINING tf.saved_model.TRAINING
tf.saved_model.utils.build_tensor_info tf.saved_model.build_tensor_info
tf.saved_model.utils.get_tensor_from_tensor_info tf.saved_model.get_tensor_from_tensor_info
tf.scalar_mul tf.math.scalar_mul
tf.serialize_many_sparse tf.io.serialize_many_sparse
tf.serialize_sparse tf.io.serialize_sparse
tf.set_random_seed tf.random.set_random_seed
tf.sign tf.math.sign
tf.space_to_batch tf.nn.space_to_batch
tf.space_to_depth tf.nn.space_to_depth
tf.sparse_add tf.sparse.add
tf.sparse_concat tf.sparse.concat
tf.sparse_fill_empty_rows tf.sparse.fill_empty_rows
tf.sparse_mask tf.sparse.mask
tf.sparse_maximum tf.sparse.maximum
tf.sparse_merge tf.sparse.merge
tf.sparse_minimum tf.sparse.minimum
tf.sparse_placeholder tf.sparse.placeholder
tf.sparse_reduce_max tf.sparse.reduce_max
tf.sparse_reduce_max_sparse tf.sparse.reduce_max_sparse
tf.sparse_reduce_sum tf.sparse.reduce_sum
tf.sparse_reduce_sum_sparse tf.sparse.reduce_sum_sparse
tf.sparse_reorder tf.sparse.reorder
tf.sparse_reset_shape tf.sparse.reset_shape
tf.sparse_reshape tf.sparse.reshape
tf.sparse_retain tf.sparse.retain
tf.sparse_segment_mean tf.sparse.segment_mean
tf.sparse_segment_sqrt_n tf.sparse.segment_sqrt_n
tf.sparse_segment_sum tf.sparse.segment_sum
tf.sparse_slice tf.sparse.slice
tf.sparse_softmax tf.sparse.softmax
tf.sparse_split tf.sparse.split
tf.sparse_tensor_dense_matmul tf.sparse.matmul
tf.sparse_tensor_to_dense tf.sparse.to_dense
tf.sparse_to_indicator tf.sparse.to_indicator
tf.sparse_transpose tf.sparse.transpose
tf.sqrt tf.math.sqrt
tf.square tf.math.square
tf.string tf.dtypes.string
tf.string_split tf.strings.split
tf.subtract tf.math.subtract
tf.tables_initializer tf.initializers.tables_initializer
tf.tanh tf.math.tanh, tf.nn.tanh
tf.train.match_filenames_once tf.io.match_filenames_once
tf.train.write_graph tf.io.write_graph
tf.truediv tf.math.truediv
tf.truncated_normal tf.random.truncated_normal
tf.truncatediv tf.math.truncatediv
tf.truncatemod tf.math.truncatemod
tf.uint16 tf.dtypes.uint16
tf.uint32 tf.dtypes.uint32
tf.uint64 tf.dtypes.uint64
tf.uint8 tf.dtypes.uint8
tf.unsorted_segment_mean tf.math.unsorted_segment_mean
tf.unsorted_segment_sqrt_n tf.math.unsorted_segment_sqrt_n
tf.variant tf.dtypes.variant
tf.verify_tensor_all_finite tf.debugging.verify_tensor_all_finite

Appendix 2: Deprecated Endpoints

In addition to symbols in this table, we plan to deprecate all symbols under tf.logging (See Deprecated namespaces section above).

Symbol that will be removed Replacement
tf.COMPILER_VERSION replace with tf.version.COMPILER_VERSION
tf.CXX11_ABI_FLAG replace with tf.sysconfig.CXX11_ABI_FLAG
tf.Event replace with tf.summary.Event
tf.GIT_VERSION replace with tf.version.GIT_VERSION
tf.GRAPH_DEF_VERSION replace with tf.version.GRAPH_DEF_VERSION
tf.GRAPH_DEF_VERSION_MIN_CONSUMER replace with tf.version.GRAPH_DEF_VERSION_MIN_CONSUMER
tf.GRAPH_DEF_VERSION_MIN_PRODUCER replace with tf.version.GRAPH_DEF_VERSION_MIN_PRODUCER
tf.HistogramProto replace with tf.summary.HistogramProto
tf.MONOLITHIC_BUILD replace with tf.sysconfig.MONOLITHIC_BUILD
tf.OpError replace with tf.errors.OpError
tf.PaddingFIFOQueue replace with tf.io.PaddingFIFOQueue
tf.PriorityQueue replace with tf.io.PriorityQueue
tf.QueueBase replace with tf.io.QueueBase
tf.RandomShuffleQueue replace with tf.io.RandomShuffleQueue
tf.SparseConditionalAccumulator replace with tf.sparse.SparseConditionalAccumulator
tf.SparseFeature replace with tf.io.SparseFeature
tf.SummaryMetadata replace with tf.summary.SummaryMetadata
tf.VERSION replace with tf.version.VERSION
tf.accumulate_n replace with tf.math.accumulate_n
tf.angle replace with tf.math.angle
tf.assert_greater_equal replace with tf.debugging.assert_greater_equal
tf.assert_integer replace with tf.debugging.assert_integer
tf.assert_less_equal replace with tf.debugging.assert_less_equal
tf.assert_near replace with tf.debugging.assert_near
tf.assert_negative replace with tf.debugging.assert_negative
tf.assert_non_negative replace with tf.debugging.assert_non_negative
tf.assert_non_positive replace with tf.debugging.assert_non_positive
tf.assert_none_equal replace with tf.debugging.assert_none_equal
tf.assert_positive replace with tf.debugging.assert_positive
tf.assert_proper_iterable replace with tf.debugging.assert_proper_iterable
tf.assert_rank_at_least replace with tf.debugging.assert_rank_at_least
tf.assert_rank_in replace with tf.debugging.assert_rank_in
tf.assert_same_float_dtype replace with tf.debugging.assert_same_float_dtype
tf.assert_scalar replace with tf.debugging.assert_scalar
tf.assert_type replace with tf.debugging.assert_type
tf.betainc replace with tf.math.betainc
tf.bincount replace with tf.math.bincount
tf.ceil replace with tf.math.ceil
tf.cholesky replace with tf.linalg.cholesky
tf.cholesky_solve replace with tf.linalg.cholesky_solve
tf.confusion_matrix replace with tf.train.confusion_matrix
tf.conj replace with tf.math.conj
tf.cross replace with tf.linalg.cross
tf.cumprod replace with tf.math.cumprod
tf.decode_base64 replace with tf.io.decode_base64
tf.decode_compressed replace with tf.io.decode_compressed
tf.decode_csv replace with tf.io.decode_csv
tf.decode_json_example replace with tf.io.decode_json_example
tf.depth_to_space replace with tf.nn.depth_to_space
tf.deserialize_many_sparse replace with tf.io.deserialize_many_sparse
tf.diag_part replace with tf.linalg.tensor_diag_part
tf.digamma replace with tf.math.digamma
tf.encode_base64 replace with tf.io.encode_base64
tf.erf replace with tf.math.erf
tf.erfc replace with tf.math.erfc
tf.expm1 replace with tf.math.expm1
tf.extract_image_patches replace with tf.image.extract_image_patches
tf.fake_quant_with_min_max_args replace with tf.quantization.fake_quant_with_min_max_args
tf.fake_quant_with_min_max_args_gradient replace with tf.quantization.fake_quant_with_min_max_args_gradient
tf.fake_quant_with_min_max_vars replace with tf.quantization.fake_quant_with_min_max_vars
tf.fake_quant_with_min_max_vars_gradient replace with tf.quantization.fake_quant_with_min_max_vars_gradient
tf.fake_quant_with_min_max_vars_per_channel replace with tf.quantization.fake_quant_with_min_max_vars_per_channel
tf.fake_quant_with_min_max_vars_per_channel_gradient replace with tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient
tf.fft replace with tf.spectral.fft
tf.fft2d replace with tf.spectral.fft2d
tf.fft3d replace with tf.spectral.fft3d
tf.floordiv replace with tf.math.floordiv
tf.floormod replace with tf.math.floormod
tf.get_seed replace with tf.random.get_seed
tf.global_norm replace with tf.linalg.global_norm
tf.glorot_normal_initializer replace with tf.initializers.glorot_normal
tf.ifft replace with tf.spectral.ifft
tf.ifft2d replace with tf.spectral.ifft2d
tf.ifft3d replace with tf.spectral.ifft3d
tf.igamma replace with tf.math.igamma
tf.igammac replace with tf.math.igammac
tf.imag replace with tf.math.imag
tf.invert_permutation replace with tf.math.invert_permutation
tf.is_finite replace with tf.debugging.is_finite
tf.is_inf replace with tf.debugging.is_inf
tf.is_non_decreasing replace with tf.debugging.is_non_decreasing
tf.is_numeric_tensor replace with tf.debugging.is_numeric_tensor
tf.is_strictly_increasing replace with tf.debugging.is_strictly_increasing
tf.lbeta replace with tf.math.lbeta
tf.lgamma replace with tf.math.lgamma
tf.log_sigmoid replace with tf.math.log_sigmoid
tf.logical_xor replace with tf.math.logical_xor
tf.manip.batch_to_space_nd replace with tf.batch_to_space_nd
tf.manip.gather_nd replace with tf.gather_nd
tf.manip.reshape replace with tf.reshape
tf.manip.roll replace with tf.roll
tf.manip.scatter_nd replace with tf.scatter_nd
tf.manip.space_to_batch_nd replace with tf.space_to_batch_nd
tf.manip.tile replace with tf.tile
tf.matching_files replace with tf.io.matching_files
tf.matrix_band_part replace with tf.linalg.matrix_band_part
tf.matrix_determinant replace with tf.linalg.det
tf.matrix_diag replace with tf.linalg.diag
tf.matrix_diag_part replace with tf.linalg.diag_part
tf.matrix_inverse replace with tf.linalg.matrix_inverse
tf.matrix_set_diag replace with tf.linalg.set_diag
tf.matrix_solve replace with tf.linalg.solve
tf.matrix_solve_ls replace with tf.linalg.matrix_solve_ls
tf.matrix_transpose replace with tf.linalg.transpose
tf.matrix_triangular_solve replace with tf.linalg.triangular_solve
tf.nn.log_uniform_candidate_sampler replace with tf.random.log_uniform_candidate_sampler
tf.nn.uniform_candidate_sampler replace with tf.random.uniform_candidate_sampler
tf.orthogonal_initializer replace with tf.initializers.orthogonal_initializer
tf.parse_tensor replace with tf.io.parse_tensor
tf.polygamma replace with tf.math.polygamma
tf.python_io.TFRecordCompressionType replace with tf.io.TFRecordCompressionType
tf.python_io.TFRecordOptions replace with tf.io.TFRecordOptions
tf.qr replace with tf.linalg.qr
tf.quantize_v2 replace with tf.quantization.quantize_v2
tf.quantized_concat replace with tf.quantization.quantized_concat
tf.random_gamma replace with tf.random.random_gamma
tf.random_poisson replace with tf.random.random_poisson
tf.read_file replace with tf.io.read_file
tf.real replace with tf.math.real
tf.realdiv replace with tf.math.realdiv
tf.reciprocal replace with tf.math.reciprocal
tf.reduce_join replace with tf.math.reduce_join
tf.regex_replace replace with tf.strings.regex_replace
tf.rint replace with tf.math.rint
tf.rsqrt replace with tf.math.rsqrt
tf.saved_model.constants.ASSETS_DIRECTORY replace with tf.saved_model.ASSETS_DIRECTORY
tf.saved_model.constants.ASSETS_KEY replace with tf.saved_model.ASSETS_KEY
tf.saved_model.constants.LEGACY_INIT_OP_KEY replace with tf.saved_model.LEGACY_INIT_OP_KEY
tf.saved_model.constants.MAIN_OP_KEY replace with tf.saved_model.MAIN_OP_KEY
tf.saved_model.constants.SAVED_MODEL_FILENAME_PB replace with tf.saved_model.SAVED_MODEL_FILENAME_PB
tf.saved_model.constants.SAVED_MODEL_FILENAME_PBTXT replace with tf.saved_model.SAVED_MODEL_FILENAME_PBTXT
tf.saved_model.constants.SAVED_MODEL_SCHEMA_VERSION replace with tf.saved_model.SAVED_MODEL_SCHEMA_VERSION
tf.saved_model.constants.VARIABLES_DIRECTORY replace with tf.saved_model.VARIABLES_DIRECTORY
tf.saved_model.constants.VARIABLES_FILENAME replace with tf.saved_model.VARIABLES_FILENAME
tf.saved_model.loader.maybe_saved_model_directory replace with tf.saved_model.maybe_saved_model_directory
tf.saved_model.main_op.main_op replace with tf.saved_model.main_op
tf.saved_model.main_op.main_op_with_restore replace with tf.saved_model.main_op_with_restore
tf.saved_model.signature_constants.CLASSIFY_INPUTS replace with tf.saved_model.CLASSIFY_INPUTS
tf.saved_model.signature_constants.CLASSIFY_METHOD_NAME replace with tf.saved_model.CLASSIFY_METHOD_NAME
tf.saved_model.signature_constants.CLASSIFY_OUTPUT_CLASSES replace with tf.saved_model.CLASSIFY_OUTPUT_CLASSES
tf.saved_model.signature_constants.CLASSIFY_OUTPUT_SCORES replace with tf.saved_model.CLASSIFY_OUTPUT_SCORES
tf.saved_model.signature_constants.PREDICT_INPUTS replace with tf.saved_model.PREDICT_INPUTS
tf.saved_model.signature_constants.PREDICT_METHOD_NAME replace with tf.saved_model.PREDICT_METHOD_NAME
tf.saved_model.signature_constants.PREDICT_OUTPUTS replace with tf.saved_model.PREDICT_OUTPUTS
tf.saved_model.signature_constants.REGRESS_INPUTS replace with tf.saved_model.REGRESS_INPUTS
tf.saved_model.signature_constants.REGRESS_METHOD_NAME replace with tf.saved_model.REGRESS_METHOD_NAME
tf.saved_model.signature_constants.REGRESS_OUTPUTS replace with tf.saved_model.REGRESS_OUTPUTS
tf.saved_model.signature_def_utils.classification_signature_def replace with tf.saved_model.classification_signature_def
tf.saved_model.signature_def_utils.is_valid_signature replace with tf.saved_model.is_valid_signature
tf.saved_model.signature_def_utils.predict_signature_def replace with tf.saved_model.predict_signature_def
tf.saved_model.signature_def_utils.regression_signature_def replace with tf.saved_model.regression_signature_def
tf.saved_model.tag_constants.GPU replace with tf.saved_model.GPU
tf.saved_model.tag_constants.TPU replace with tf.saved_model.TPU
tf.saved_model.tag_constants.TRAINING replace with tf.saved_model.TRAINING
tf.saved_model.utils.get_tensor_from_tensor_info replace with tf.saved_model.get_tensor_from_tensor_info
tf.segment_max replace with tf.math.segment_max
tf.segment_mean replace with tf.math.segment_mean
tf.segment_min replace with tf.math.segment_min
tf.segment_prod replace with tf.math.segment_prod
tf.segment_sum replace with tf.math.segment_sum
tf.self_adjoint_eig replace with tf.linalg.self_adjoint_eig
tf.self_adjoint_eigvals replace with tf.linalg.self_adjoint_eigvals
tf.serialize_many_sparse replace with tf.io.serialize_many_sparse
tf.serialize_sparse replace with tf.io.serialize_sparse
tf.space_to_batch replace with tf.nn.space_to_batch
tf.space_to_depth replace with tf.nn.space_to_depth
tf.sparse_add replace with tf.sparse.add
tf.sparse_concat replace with tf.sparse.concat
tf.sparse_fill_empty_rows replace with tf.sparse.fill_empty_rows
tf.sparse_mask replace with tf.sparse.mask
tf.sparse_maximum replace with tf.sparse.maximum
tf.sparse_merge replace with tf.sparse.merge
tf.sparse_minimum replace with tf.sparse.minimum
tf.sparse_placeholder replace with tf.sparse.placeholder
tf.sparse_reduce_max replace with tf.sparse.reduce_max
tf.sparse_reduce_max_sparse replace with tf.sparse.reduce_max_sparse
tf.sparse_reduce_sum replace with tf.sparse.reduce_sum
tf.sparse_reduce_sum_sparse replace with tf.sparse.reduce_sum_sparse
tf.sparse_reorder replace with tf.sparse.reorder
tf.sparse_reset_shape replace with tf.sparse.reset_shape
tf.sparse_reshape replace with tf.sparse.reshape
tf.sparse_segment_mean replace with tf.sparse.segment_mean
tf.sparse_segment_sqrt_n replace with tf.sparse.segment_sqrt_n
tf.sparse_segment_sum replace with tf.sparse.segment_sum
tf.sparse_slice replace with tf.sparse.slice
tf.sparse_softmax replace with tf.sparse.softmax
tf.sparse_split replace with tf.sparse.split
tf.sparse_tensor_dense_matmul replace with tf.sparse.matmul
tf.sparse_to_dense replace with tf.sparse.to_dense which takes SparseTensor
object
tf.sparse_to_indicator replace with tf.sparse.to_indicator
tf.sparse_tensor_to_dense replace with tf.sparse.to_dense
tf.sparse_transpose replace with tf.sparse.transpose
tf.string_join replace with tf.strings.join
tf.string_strip replace with tf.strings.strip
tf.string_to_hash_bucket replace with tf.strings.to_hash_bucket
tf.string_to_hash_bucket_fast replace with tf.strings.to_hash_bucket_fast
tf.string_to_hash_bucket_strong replace with tf.strings.to_hash_bucket_strong
tf.substr replace with tf.strings.substr
tf.svd replace with tf.linalg.svd
tf.trace replace with tf.linalg.trace
tf.train.VocabInfo replace with tf.estimator.VocabInfo
tf.train.match_filenames_once replace with tf.io.match_filenames_once
tf.truncatediv replace with tf.math.truncatediv
tf.truncatemod replace with tf.math.truncatemod
tf.uniform_unit_scaling_initializer replace with tf.initializers.uniform_unit_scaling
tf.unsorted_segment_max replace with tf.math.unsorted_segment_max
tf.unsorted_segment_mean replace with tf.math.unsorted_segment_mean
tf.unsorted_segment_min replace with tf.math.unsorted_segment_min
tf.unsorted_segment_prod replace with tf.math.unsorted_segment_prod
tf.unsorted_segment_sqrt_n replace with tf.math.unsorted_segment_sqrt_n
tf.unsorted_segment_sum replace with tf.math.unsorted_segment_sum
tf.variance_scaling_initializer replace with tf.initializers.variance_scaling
tf.verify_tensor_all_finite replace with tf.debugging.verify_tensor_all_finite
tf.write_file replace with tf.io.write_file
tf.zeta replace with tf.math.zeta
You can’t perform that action at this time.