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| # Copyright 2017 The TensorFlow Authors. All Rights Reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # ============================================================================== | |
| """Scalar summaries and TensorFlow operations to create them. | |
| A scalar summary stores a single floating-point value, as a rank-0 | |
| tensor. | |
| """ | |
| import numpy as np | |
| from tensorboard.plugins.scalar import metadata | |
| from tensorboard.plugins.scalar import summary_v2 | |
| # Export V2 versions. | |
| scalar = summary_v2.scalar | |
| scalar_pb = summary_v2.scalar_pb | |
| def op(name, data, display_name=None, description=None, collections=None): | |
| """Create a legacy scalar summary op. | |
| Arguments: | |
| name: A unique name for the generated summary node. | |
| data: A real numeric rank-0 `Tensor`. Must have `dtype` castable | |
| to `float32`. | |
| display_name: Optional name for this summary in TensorBoard, as a | |
| constant `str`. Defaults to `name`. | |
| description: Optional long-form description for this summary, as a | |
| constant `str`. Markdown is supported. Defaults to empty. | |
| collections: Optional list of graph collections keys. The new | |
| summary op is added to these collections. Defaults to | |
| `[Graph Keys.SUMMARIES]`. | |
| Returns: | |
| A TensorFlow summary op. | |
| """ | |
| # TODO(nickfelt): remove on-demand imports once dep situation is fixed. | |
| import tensorflow.compat.v1 as tf | |
| if display_name is None: | |
| display_name = name | |
| summary_metadata = metadata.create_summary_metadata( | |
| display_name=display_name, description=description | |
| ) | |
| with tf.name_scope(name): | |
| with tf.control_dependencies([tf.assert_scalar(data)]): | |
| return tf.summary.tensor_summary( | |
| name="scalar_summary", | |
| tensor=tf.cast(data, tf.float32), | |
| collections=collections, | |
| summary_metadata=summary_metadata, | |
| ) | |
| def pb(name, data, display_name=None, description=None): | |
| """Create a legacy scalar summary protobuf. | |
| Arguments: | |
| name: A unique name for the generated summary, including any desired | |
| name scopes. | |
| data: A rank-0 `np.array` or array-like form (so raw `int`s and | |
| `float`s are fine, too). | |
| display_name: Optional name for this summary in TensorBoard, as a | |
| `str`. Defaults to `name`. | |
| description: Optional long-form description for this summary, as a | |
| `str`. Markdown is supported. Defaults to empty. | |
| Returns: | |
| A `tf.Summary` protobuf object. | |
| """ | |
| # TODO(nickfelt): remove on-demand imports once dep situation is fixed. | |
| import tensorflow.compat.v1 as tf | |
| data = np.array(data) | |
| if data.shape != (): | |
| raise ValueError( | |
| "Expected scalar shape for data, saw shape: %s." % data.shape | |
| ) | |
| if data.dtype.kind not in ("b", "i", "u", "f"): # bool, int, uint, float | |
| raise ValueError("Cast %s to float is not supported" % data.dtype.name) | |
| tensor = tf.make_tensor_proto(data.astype(np.float32)) | |
| if display_name is None: | |
| display_name = name | |
| summary_metadata = metadata.create_summary_metadata( | |
| display_name=display_name, description=description | |
| ) | |
| tf_summary_metadata = tf.SummaryMetadata.FromString( | |
| summary_metadata.SerializeToString() | |
| ) | |
| summary = tf.Summary() | |
| summary.value.add( | |
| tag="%s/scalar_summary" % name, | |
| metadata=tf_summary_metadata, | |
| tensor=tensor, | |
| ) | |
| return summary | |