160 lines
5.6 KiB
Python
160 lines
5.6 KiB
Python
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Classes and functions for handling the DownloadData API call."""
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import csv
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import io
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import math
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from tensorboard.plugins.hparams import error
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class OutputFormat:
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"""An enum used to list the valid output formats for API calls."""
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JSON = "json"
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CSV = "csv"
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LATEX = "latex"
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class Handler:
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"""Handles a DownloadData request."""
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def __init__(
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self,
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context,
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experiment,
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session_groups,
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response_format,
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columns_visibility,
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):
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"""Constructor.
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Args:
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context: A backend_context.Context instance.
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experiment: Experiment proto.
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session_groups: ListSessionGroupsResponse proto.
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response_format: A string in the OutputFormat enum.
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columns_visibility: A list of boolean values to filter columns.
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"""
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self._context = context
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self._experiment = experiment
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self._session_groups = session_groups
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self._response_format = response_format
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self._columns_visibility = columns_visibility
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def run(self):
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"""Handles the request specified on construction.
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Returns:
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A response body.
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A mime type (string) for the response.
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"""
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experiment = self._experiment
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session_groups = self._session_groups
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response_format = self._response_format
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visibility = self._columns_visibility
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header = []
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for hparam_info in experiment.hparam_infos:
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header.append(hparam_info.display_name or hparam_info.name)
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for metric_info in experiment.metric_infos:
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header.append(metric_info.display_name or metric_info.name.tag)
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def _filter_columns(row):
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return [value for value, visible in zip(row, visibility) if visible]
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header = _filter_columns(header)
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rows = []
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def _get_value(value):
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if value.HasField("number_value"):
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return value.number_value
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if value.HasField("string_value"):
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return value.string_value
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if value.HasField("bool_value"):
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return value.bool_value
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# hyperparameter values can be optional in a session group
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return ""
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def _get_metric_id(metric):
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return metric.group + "." + metric.tag
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for group in session_groups.session_groups:
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row = []
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for hparam_info in experiment.hparam_infos:
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row.append(_get_value(group.hparams[hparam_info.name]))
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metric_values = {}
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for metric_value in group.metric_values:
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metric_id = _get_metric_id(metric_value.name)
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metric_values[metric_id] = metric_value.value
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for metric_info in experiment.metric_infos:
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metric_id = _get_metric_id(metric_info.name)
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row.append(metric_values.get(metric_id))
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rows.append(_filter_columns(row))
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if response_format == OutputFormat.JSON:
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mime_type = "application/json"
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body = dict(header=header, rows=rows)
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elif response_format == OutputFormat.LATEX:
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def latex_format(value):
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if value is None:
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return "-"
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elif isinstance(value, int):
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return "$%d$" % value
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elif isinstance(value, float):
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if math.isnan(value):
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return r"$\mathrm{NaN}$"
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if value in (float("inf"), float("-inf")):
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return r"$%s\infty$" % ("-" if value < 0 else "+")
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scientific = "%.3g" % value
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if "e" in scientific:
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coefficient, exponent = scientific.split("e")
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return "$%s\\cdot 10^{%d}$" % (
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coefficient,
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int(exponent),
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)
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return "$%s$" % scientific
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return value.replace("_", "\\_").replace("%", "\\%")
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mime_type = "application/x-latex"
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top_part = "\\begin{table}[tbp]\n\\begin{tabular}{%s}\n" % (
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"l" * len(header)
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)
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header_part = (
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" & ".join(map(latex_format, header)) + " \\\\ \\hline\n"
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)
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middle_part = "".join(
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" & ".join(map(latex_format, row)) + " \\\\\n" for row in rows
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)
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bottom_part = "\\hline\n\\end{tabular}\n\\end{table}\n"
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body = top_part + header_part + middle_part + bottom_part
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elif response_format == OutputFormat.CSV:
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string_io = io.StringIO()
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writer = csv.writer(string_io)
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writer.writerow(header)
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writer.writerows(rows)
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body = string_io.getvalue()
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mime_type = "text/csv"
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else:
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raise error.HParamsError(
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"Invalid reponses format: %s" % response_format
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)
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return body, mime_type
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