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mlperf/training | reinforcement/tensorflow/minigo/mcts.py | MCTSNode.maybe_add_child | def maybe_add_child(self, fcoord):
""" Adds child node for fcoord if it doesn't already exist, and returns it. """
if fcoord not in self.children:
new_position = self.position.play_move(
coords.from_flat(fcoord))
self.children[fcoord] = MCTSNode(
n... | python | def maybe_add_child(self, fcoord):
""" Adds child node for fcoord if it doesn't already exist, and returns it. """
if fcoord not in self.children:
new_position = self.position.play_move(
coords.from_flat(fcoord))
self.children[fcoord] = MCTSNode(
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mlperf/training | reinforcement/tensorflow/minigo/mcts.py | MCTSNode.add_virtual_loss | def add_virtual_loss(self, up_to):
"""Propagate a virtual loss up to the root node.
Args:
up_to: The node to propagate until. (Keep track of this! You'll
need it to reverse the virtual loss later.)
"""
self.losses_applied += 1
# This is a "win" for th... | python | def add_virtual_loss(self, up_to):
"""Propagate a virtual loss up to the root node.
Args:
up_to: The node to propagate until. (Keep track of this! You'll
need it to reverse the virtual loss later.)
"""
self.losses_applied += 1
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mlperf/training | reinforcement/tensorflow/minigo/mcts.py | MCTSNode.backup_value | def backup_value(self, value, up_to):
"""Propagates a value estimation up to the root node.
Args:
value: the value to be propagated (1 = black wins, -1 = white wins)
up_to: the node to propagate until.
"""
self.N += 1
self.W += value
if self.paren... | python | def backup_value(self, value, up_to):
"""Propagates a value estimation up to the root node.
Args:
value: the value to be propagated (1 = black wins, -1 = white wins)
up_to: the node to propagate until.
"""
self.N += 1
self.W += value
if self.paren... | [
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mlperf/training | reinforcement/tensorflow/minigo/mcts.py | MCTSNode.is_done | def is_done(self):
"""True if the last two moves were Pass or if the position is at a move
greater than the max depth."""
return self.position.is_game_over() or self.position.n >= FLAGS.max_game_length | python | def is_done(self):
"""True if the last two moves were Pass or if the position is at a move
greater than the max depth."""
return self.position.is_game_over() or self.position.n >= FLAGS.max_game_length | [
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mlperf/training | reinforcement/tensorflow/minigo/mcts.py | MCTSNode.children_as_pi | def children_as_pi(self, squash=False):
"""Returns the child visit counts as a probability distribution, pi
If squash is true, exponentiate the probabilities by a temperature
slightly larger than unity to encourage diversity in early play and
hopefully to move away from 3-3s
"""
... | python | def children_as_pi(self, squash=False):
"""Returns the child visit counts as a probability distribution, pi
If squash is true, exponentiate the probabilities by a temperature
slightly larger than unity to encourage diversity in early play and
hopefully to move away from 3-3s
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mlperf/training | reinforcement/tensorflow/minigo/mcts.py | MCTSNode.mvp_gg | def mvp_gg(self):
""" Returns most visited path in go-gui VAR format e.g. 'b r3 w c17..."""
output = []
for node in self.most_visited_path_nodes():
if max(node.child_N) <= 1:
break
output.append(coords.to_gtp(coords.from_flat(node.fmove)))
return '... | python | def mvp_gg(self):
""" Returns most visited path in go-gui VAR format e.g. 'b r3 w c17..."""
output = []
for node in self.most_visited_path_nodes():
if max(node.child_N) <= 1:
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output.append(coords.to_gtp(coords.from_flat(node.fmove)))
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mlperf/training | reinforcement/tensorflow/minigo/gtp_engine.py | _convert_args | def _convert_args(handler, args):
"""Convert a list of command arguments to types specified by the handler.
Args:
handler: a command handler function.
args: the list of string arguments to pass to handler.
Returns:
A new list containing `args` that have been converted to the expected typ... | python | def _convert_args(handler, args):
"""Convert a list of command arguments to types specified by the handler.
Args:
handler: a command handler function.
args: the list of string arguments to pass to handler.
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mlperf/training | reinforcement/tensorflow/minigo/gtp_engine.py | Engine.add_cmd_handler | def add_cmd_handler(self, handler_obj):
"""Registers a new command handler object.
All methods on `handler_obj` whose name starts with "cmd_" are
registered as a GTP command. For example, the method cmd_genmove will
be invoked when the engine receives a genmove command.
Args:
... | python | def add_cmd_handler(self, handler_obj):
"""Registers a new command handler object.
All methods on `handler_obj` whose name starts with "cmd_" are
registered as a GTP command. For example, the method cmd_genmove will
be invoked when the engine receives a genmove command.
Args:
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | _pad_tensors_to_same_length | def _pad_tensors_to_same_length(x, y):
"""Pad x and y so that the results have the same length (second dimension)."""
with tf.name_scope("pad_to_same_length"):
x_length = tf.shape(x)[1]
y_length = tf.shape(y)[1]
max_length = tf.maximum(x_length, y_length)
x = tf.pad(x, [[0, 0], [0, max_length - x_... | python | def _pad_tensors_to_same_length(x, y):
"""Pad x and y so that the results have the same length (second dimension)."""
with tf.name_scope("pad_to_same_length"):
x_length = tf.shape(x)[1]
y_length = tf.shape(y)[1]
max_length = tf.maximum(x_length, y_length)
x = tf.pad(x, [[0, 0], [0, max_length - x_... | [
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | padded_cross_entropy_loss | def padded_cross_entropy_loss(logits, labels, smoothing, vocab_size):
"""Calculate cross entropy loss while ignoring padding.
Args:
logits: Tensor of size [batch_size, length_logits, vocab_size]
labels: Tensor of size [batch_size, length_labels]
smoothing: Label smoothing constant, used to determine th... | python | def padded_cross_entropy_loss(logits, labels, smoothing, vocab_size):
"""Calculate cross entropy loss while ignoring padding.
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logits: Tensor of size [batch_size, length_logits, vocab_size]
labels: Tensor of size [batch_size, length_labels]
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vocab_size: int size of the vocabulary
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | _convert_to_eval_metric | def _convert_to_eval_metric(metric_fn):
"""Wrap a metric fn that returns scores and weights as an eval metric fn.
The input metric_fn returns values for the current batch. The wrapper
aggregates the return values collected over all of the batches evaluated.
Args:
metric_fn: function that returns scores an... | python | def _convert_to_eval_metric(metric_fn):
"""Wrap a metric fn that returns scores and weights as an eval metric fn.
The input metric_fn returns values for the current batch. The wrapper
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | get_eval_metrics | def get_eval_metrics(logits, labels, params):
"""Return dictionary of model evaluation metrics."""
metrics = {
"accuracy": _convert_to_eval_metric(padded_accuracy)(logits, labels),
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logits, labels),
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"""Return dictionary of model evaluation metrics."""
metrics = {
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | padded_accuracy | def padded_accuracy(logits, labels):
"""Percentage of times that predictions matches labels on non-0s."""
with tf.variable_scope("padded_accuracy", values=[logits, labels]):
logits, labels = _pad_tensors_to_same_length(logits, labels)
weights = tf.to_float(tf.not_equal(labels, 0))
outputs = tf.to_int32(... | python | def padded_accuracy(logits, labels):
"""Percentage of times that predictions matches labels on non-0s."""
with tf.variable_scope("padded_accuracy", values=[logits, labels]):
logits, labels = _pad_tensors_to_same_length(logits, labels)
weights = tf.to_float(tf.not_equal(labels, 0))
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | padded_accuracy_topk | def padded_accuracy_topk(logits, labels, k):
"""Percentage of times that top-k predictions matches labels on non-0s."""
with tf.variable_scope("padded_accuracy_topk", values=[logits, labels]):
logits, labels = _pad_tensors_to_same_length(logits, labels)
weights = tf.to_float(tf.not_equal(labels, 0))
eff... | python | def padded_accuracy_topk(logits, labels, k):
"""Percentage of times that top-k predictions matches labels on non-0s."""
with tf.variable_scope("padded_accuracy_topk", values=[logits, labels]):
logits, labels = _pad_tensors_to_same_length(logits, labels)
weights = tf.to_float(tf.not_equal(labels, 0))
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | padded_sequence_accuracy | def padded_sequence_accuracy(logits, labels):
"""Percentage of times that predictions matches labels everywhere (non-0)."""
with tf.variable_scope("padded_sequence_accuracy", values=[logits, labels]):
logits, labels = _pad_tensors_to_same_length(logits, labels)
weights = tf.to_float(tf.not_equal(labels, 0))... | python | def padded_sequence_accuracy(logits, labels):
"""Percentage of times that predictions matches labels everywhere (non-0)."""
with tf.variable_scope("padded_sequence_accuracy", values=[logits, labels]):
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | padded_neg_log_perplexity | def padded_neg_log_perplexity(logits, labels, vocab_size):
"""Average log-perplexity excluding padding 0s. No smoothing."""
num, den = padded_cross_entropy_loss(logits, labels, 0, vocab_size)
return -num, den | python | def padded_neg_log_perplexity(logits, labels, vocab_size):
"""Average log-perplexity excluding padding 0s. No smoothing."""
num, den = padded_cross_entropy_loss(logits, labels, 0, vocab_size)
return -num, den | [
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | bleu_score | def bleu_score(logits, labels):
"""Approximate BLEU score computation between labels and predictions.
An approximate BLEU scoring method since we do not glue word pieces or
decode the ids and tokenize the output. By default, we use ngram order of 4
and use brevity penalty. Also, this does not have beam search.... | python | def bleu_score(logits, labels):
"""Approximate BLEU score computation between labels and predictions.
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | _get_ngrams_with_counter | def _get_ngrams_with_counter(segment, max_order):
"""Extracts all n-grams up to a given maximum order from an input segment.
Args:
segment: text segment from which n-grams will be extracted.
max_order: maximum length in tokens of the n-grams returned by this
methods.
Returns:
The Counter con... | python | def _get_ngrams_with_counter(segment, max_order):
"""Extracts all n-grams up to a given maximum order from an input segment.
Args:
segment: text segment from which n-grams will be extracted.
max_order: maximum length in tokens of the n-grams returned by this
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | compute_bleu | def compute_bleu(reference_corpus, translation_corpus, max_order=4,
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"""Computes BLEU score of translated segments against one or more references.
Args:
reference_corpus: list of references for each translation. Each
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... | python | def compute_bleu(reference_corpus, translation_corpus, max_order=4,
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Args:
reference_corpus: list of references for each translation. Each
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | rouge_2_fscore | def rouge_2_fscore(logits, labels):
"""ROUGE-2 F1 score computation between labels and predictions.
This is an approximate ROUGE scoring method since we do not glue word pieces
or decode the ids and tokenize the output.
Args:
logits: tensor, model predictions
labels: tensor, gold output.
Returns:
... | python | def rouge_2_fscore(logits, labels):
"""ROUGE-2 F1 score computation between labels and predictions.
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or decode the ids and tokenize the output.
Args:
logits: tensor, model predictions
labels: tensor, gold output.
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | rouge_n | def rouge_n(eval_sentences, ref_sentences, n=2):
"""Computes ROUGE-N f1 score of two text collections of sentences.
Source: https://www.microsoft.com/en-us/research/publication/
rouge-a-package-for-automatic-evaluation-of-summaries/
Args:
eval_sentences: Predicted sentences.
ref_sentences: Sentences f... | python | def rouge_n(eval_sentences, ref_sentences, n=2):
"""Computes ROUGE-N f1 score of two text collections of sentences.
Source: https://www.microsoft.com/en-us/research/publication/
rouge-a-package-for-automatic-evaluation-of-summaries/
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mlperf/training | translation/tensorflow/transformer/utils/metrics.py | rouge_l_fscore | def rouge_l_fscore(predictions, labels):
"""ROUGE scores computation between labels and predictions.
This is an approximate ROUGE scoring method since we do not glue word pieces
or decode the ids and tokenize the output.
Args:
predictions: tensor, model predictions
labels: tensor, gold output.
Retu... | python | def rouge_l_fscore(predictions, labels):
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predictions: tensor, model predictions
labels: tensor, gold output.
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mlperf/training | single_stage_detector/ssd/bind_launch.py | parse_args | def parse_args():
"""
Helper function parsing the command line options
@retval ArgumentParser
"""
parser = ArgumentParser(description="PyTorch distributed training launch "
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"""
Helper function parsing the command line options
@retval ArgumentParser
"""
parser = ArgumentParser(description="PyTorch distributed training launch "
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mlperf/training | translation/data_download.py | download_and_extract | def download_and_extract(path, url, input_filename, target_filename):
"""Extract files from downloaded compressed archive file.
Args:
path: string directory where the files will be downloaded
url: url containing the compressed input and target files
input_filename: name of file containing data in sourc... | python | def download_and_extract(path, url, input_filename, target_filename):
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path: string directory where the files will be downloaded
url: url containing the compressed input and target files
input_filename: name of file containing data in sourc... | [
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mlperf/training | translation/data_download.py | main | def main(unused_argv):
"""Obtain training and evaluation data for the Transformer model."""
make_dir(FLAGS.raw_dir)
make_dir(FLAGS.data_dir)
# Get paths of download/extracted training and evaluation files.
print("Step 1/4: Downloading data from source")
train_files = get_raw_files(FLAGS.raw_dir, _TRAIN_DAT... | python | def main(unused_argv):
"""Obtain training and evaluation data for the Transformer model."""
make_dir(FLAGS.raw_dir)
make_dir(FLAGS.data_dir)
# Get paths of download/extracted training and evaluation files.
print("Step 1/4: Downloading data from source")
train_files = get_raw_files(FLAGS.raw_dir, _TRAIN_DAT... | [
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mlperf/training | reinforcement/tensorflow/minigo/oneoffs/prepare_bigquery.py | parse_comment_node | def parse_comment_node(comment):
# Example of a comment node. The resign threshold line appears only
# for the first move in the game; it gets preprocessed by extract_game_data
"""
Resign Threshold: -0.88
-0.0662
D4 (100) ==> D16 (14) ==> Q16 (3) ==> Q4 (1) ==> Q: -0.07149
move: action Q U P... | python | def parse_comment_node(comment):
# Example of a comment node. The resign threshold line appears only
# for the first move in the game; it gets preprocessed by extract_game_data
"""
Resign Threshold: -0.88
-0.0662
D4 (100) ==> D16 (14) ==> Q16 (3) ==> Q4 (1) ==> Q: -0.07149
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mlperf/training | object_detection/pytorch/maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py | FastRCNNLossComputation.subsample | def subsample(self, proposals, targets):
"""
This method performs the positive/negative sampling, and return
the sampled proposals.
Note: this function keeps a state.
Arguments:
proposals (list[BoxList])
targets (list[BoxList])
"""
labels... | python | def subsample(self, proposals, targets):
"""
This method performs the positive/negative sampling, and return
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Note: this function keeps a state.
Arguments:
proposals (list[BoxList])
targets (list[BoxList])
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mlperf/training | rnn_translator/pytorch/seq2seq/models/encoder.py | ResidualRecurrentEncoder.forward | def forward(self, inputs, lengths):
"""
Execute the encoder.
:param inputs: tensor with indices from the vocabulary
:param lengths: vector with sequence lengths (excluding padding)
returns: tensor with encoded sequences
"""
x = self.embedder(inputs)
# b... | python | def forward(self, inputs, lengths):
"""
Execute the encoder.
:param inputs: tensor with indices from the vocabulary
:param lengths: vector with sequence lengths (excluding padding)
returns: tensor with encoded sequences
"""
x = self.embedder(inputs)
# b... | [
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mlperf/training | reinforcement/tensorflow/minigo/ml_perf/utils.py | checked_run | async def checked_run(*cmd):
"""Run the given subprocess command in a coroutine.
Args:
*cmd: the command to run and its arguments.
Returns:
The output that the command wrote to stdout.
Raises:
RuntimeError: if the command returns a non-zero result.
"""
# Start the subprocess.
logging.info(... | python | async def checked_run(*cmd):
"""Run the given subprocess command in a coroutine.
Args:
*cmd: the command to run and its arguments.
Returns:
The output that the command wrote to stdout.
Raises:
RuntimeError: if the command returns a non-zero result.
"""
# Start the subprocess.
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mlperf/training | reinforcement/tensorflow/minigo/ml_perf/utils.py | wait | def wait(aws):
"""Waits for all of the awaitable objects (e.g. coroutines) in aws to finish.
All the awaitable objects are waited for, even if one of them raises an
exception. When one or more awaitable raises an exception, the exception from
the awaitable with the lowest index in the aws list will be reraised... | python | def wait(aws):
"""Waits for all of the awaitable objects (e.g. coroutines) in aws to finish.
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mlperf/training | compliance/verify_submission/mlperf_submission_helper/utils.py | get_subdirs | def get_subdirs(parent_path):
"""Return a list of (name, path) tuples of direct subdirectories of
parent_path, where each tuple corresponds to one subdirectory. Files
in the parent_path are excluded from the output.
"""
entries = os.listdir(parent_path)
subdirs = [(entry, os.path.join(parent_path, en... | python | def get_subdirs(parent_path):
"""Return a list of (name, path) tuples of direct subdirectories of
parent_path, where each tuple corresponds to one subdirectory. Files
in the parent_path are excluded from the output.
"""
entries = os.listdir(parent_path)
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mlperf/training | object_detection/pytorch/maskrcnn_benchmark/modeling/poolers.py | Pooler.forward | def forward(self, x, boxes):
"""
Arguments:
x (list[Tensor]): feature maps for each level
boxes (list[BoxList]): boxes to be used to perform the pooling operation.
Returns:
result (Tensor)
"""
num_levels = len(self.poolers)
rois = self.... | python | def forward(self, x, boxes):
"""
Arguments:
x (list[Tensor]): feature maps for each level
boxes (list[BoxList]): boxes to be used to perform the pooling operation.
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num_levels = len(self.poolers)
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mlperf/training | speech_recognition/data/data_loader.py | augment_audio_with_sox | def augment_audio_with_sox(path, sample_rate, tempo, gain):
"""
Changes tempo and gain of the recording with sox and loads it.
"""
with NamedTemporaryFile(suffix=".wav") as augmented_file:
augmented_filename = augmented_file.name
sox_augment_params = ["tempo", "{:.3f}".format(tempo), "ga... | python | def augment_audio_with_sox(path, sample_rate, tempo, gain):
"""
Changes tempo and gain of the recording with sox and loads it.
"""
with NamedTemporaryFile(suffix=".wav") as augmented_file:
augmented_filename = augmented_file.name
sox_augment_params = ["tempo", "{:.3f}".format(tempo), "ga... | [
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mlperf/training | speech_recognition/data/data_loader.py | load_randomly_augmented_audio | def load_randomly_augmented_audio(path, sample_rate=16000, tempo_range=(0.85, 1.15),
gain_range=(-6, 8)):
"""
Picks tempo and gain uniformly, applies it to the utterance by using sox utility.
Returns the augmented utterance.
"""
low_tempo, high_tempo = tempo_range
... | python | def load_randomly_augmented_audio(path, sample_rate=16000, tempo_range=(0.85, 1.15),
gain_range=(-6, 8)):
"""
Picks tempo and gain uniformly, applies it to the utterance by using sox utility.
Returns the augmented utterance.
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low_tempo, high_tempo = tempo_range
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mlperf/training | translation/tensorflow/transformer/transformer_main.py | model_fn | def model_fn(features, labels, mode, params):
"""Defines how to train, evaluate and predict from the transformer model."""
with tf.variable_scope("model"):
inputs, targets = features, labels
# Create model and get output logits.
model = transformer.Transformer(params, mode == tf.estimator.ModeKeys.TRAI... | python | def model_fn(features, labels, mode, params):
"""Defines how to train, evaluate and predict from the transformer model."""
with tf.variable_scope("model"):
inputs, targets = features, labels
# Create model and get output logits.
model = transformer.Transformer(params, mode == tf.estimator.ModeKeys.TRAI... | [
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mlperf/training | translation/tensorflow/transformer/transformer_main.py | get_learning_rate | def get_learning_rate(learning_rate, hidden_size, learning_rate_warmup_steps):
"""Calculate learning rate with linear warmup and rsqrt decay."""
with tf.name_scope("learning_rate"):
warmup_steps = tf.to_float(learning_rate_warmup_steps)
step = tf.to_float(tf.train.get_or_create_global_step())
learning_... | python | def get_learning_rate(learning_rate, hidden_size, learning_rate_warmup_steps):
"""Calculate learning rate with linear warmup and rsqrt decay."""
with tf.name_scope("learning_rate"):
warmup_steps = tf.to_float(learning_rate_warmup_steps)
step = tf.to_float(tf.train.get_or_create_global_step())
learning_... | [
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mlperf/training | translation/tensorflow/transformer/transformer_main.py | get_train_op | def get_train_op(loss, params):
"""Generate training operation that updates variables based on loss."""
with tf.variable_scope("get_train_op"):
mlperf_log.transformer_print(
key=mlperf_log.OPT_LR_WARMUP_STEPS,
value=params.learning_rate_warmup_steps)
learning_rate = get_learning_rate(
... | python | def get_train_op(loss, params):
"""Generate training operation that updates variables based on loss."""
with tf.variable_scope("get_train_op"):
mlperf_log.transformer_print(
key=mlperf_log.OPT_LR_WARMUP_STEPS,
value=params.learning_rate_warmup_steps)
learning_rate = get_learning_rate(
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mlperf/training | translation/tensorflow/transformer/transformer_main.py | translate_and_compute_bleu | def translate_and_compute_bleu(estimator, subtokenizer, bleu_source, bleu_ref):
"""Translate file and report the cased and uncased bleu scores."""
# Create temporary file to store translation.
tmp = tempfile.NamedTemporaryFile(delete=False)
tmp_filename = tmp.name
translate.translate_file(
estimator, s... | python | def translate_and_compute_bleu(estimator, subtokenizer, bleu_source, bleu_ref):
"""Translate file and report the cased and uncased bleu scores."""
# Create temporary file to store translation.
tmp = tempfile.NamedTemporaryFile(delete=False)
tmp_filename = tmp.name
translate.translate_file(
estimator, s... | [
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mlperf/training | translation/tensorflow/transformer/transformer_main.py | evaluate_and_log_bleu | def evaluate_and_log_bleu(estimator, bleu_writer, bleu_source, bleu_ref):
"""Calculate and record the BLEU score."""
subtokenizer = tokenizer.Subtokenizer(
os.path.join(FLAGS.data_dir, FLAGS.vocab_file))
uncased_score, cased_score = translate_and_compute_bleu(
estimator, subtokenizer, bleu_source, bl... | python | def evaluate_and_log_bleu(estimator, bleu_writer, bleu_source, bleu_ref):
"""Calculate and record the BLEU score."""
subtokenizer = tokenizer.Subtokenizer(
os.path.join(FLAGS.data_dir, FLAGS.vocab_file))
uncased_score, cased_score = translate_and_compute_bleu(
estimator, subtokenizer, bleu_source, bl... | [
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mlperf/training | translation/tensorflow/transformer/transformer_main.py | train_schedule | def train_schedule(
estimator, train_eval_iterations, single_iteration_train_steps=None,
single_iteration_train_epochs=None, bleu_source=None, bleu_ref=None,
bleu_threshold=None):
"""Train and evaluate model, and optionally compute model's BLEU score.
**Step vs. Epoch vs. Iteration**
Steps and epoch... | python | def train_schedule(
estimator, train_eval_iterations, single_iteration_train_steps=None,
single_iteration_train_epochs=None, bleu_source=None, bleu_ref=None,
bleu_threshold=None):
"""Train and evaluate model, and optionally compute model's BLEU score.
**Step vs. Epoch vs. Iteration**
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PyGithub/PyGithub | github/Team.py | Team.add_membership | def add_membership(self, member, role=github.GithubObject.NotSet):
"""
:calls: `PUT /teams/:id/memberships/:user <http://developer.github.com/v3/orgs/teams>`_
:param member: :class:`github.Nameduser.NamedUser`
:param role: string
:rtype: None
"""
assert isinstance... | python | def add_membership(self, member, role=github.GithubObject.NotSet):
"""
:calls: `PUT /teams/:id/memberships/:user <http://developer.github.com/v3/orgs/teams>`_
:param member: :class:`github.Nameduser.NamedUser`
:param role: string
:rtype: None
"""
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PyGithub/PyGithub | github/Team.py | Team.add_to_repos | def add_to_repos(self, repo):
"""
:calls: `PUT /teams/:id/repos/:org/:repo <http://developer.github.com/v3/orgs/teams>`_
:param repo: :class:`github.Repository.Repository`
:rtype: None
"""
assert isinstance(repo, github.Repository.Repository), repo
headers, data =... | python | def add_to_repos(self, repo):
"""
:calls: `PUT /teams/:id/repos/:org/:repo <http://developer.github.com/v3/orgs/teams>`_
:param repo: :class:`github.Repository.Repository`
:rtype: None
"""
assert isinstance(repo, github.Repository.Repository), repo
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PyGithub/PyGithub | github/Team.py | Team.set_repo_permission | def set_repo_permission(self, repo, permission):
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:calls: `PUT /teams/:id/repos/:org/:repo <http://developer.github.com/v3/orgs/teams>`_
:param repo: :class:`github.Repository.Repository`
:param permission: string
:rtype: None
"""
assert isinstance(repo, github... | python | def set_repo_permission(self, repo, permission):
"""
:calls: `PUT /teams/:id/repos/:org/:repo <http://developer.github.com/v3/orgs/teams>`_
:param repo: :class:`github.Repository.Repository`
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"""
:calls: `PATCH /teams/:id <http://developer.github.com/v3/orgs/teams>`_
:param name: string
:param description: string
:param permission: s... | python | def edit(self, name, description=github.GithubObject.NotSet, permission=github.GithubObject.NotSet, privacy=github.GithubObject.NotSet):
"""
:calls: `PATCH /teams/:id <http://developer.github.com/v3/orgs/teams>`_
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:param description: string
:param permission: s... | [
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PyGithub/PyGithub | github/Team.py | Team.get_members | def get_members(self, role=github.GithubObject.NotSet):
"""
:calls: `GET /teams/:id/members <https://developer.github.com/v3/teams/members/#list-team-members>`_
:param role: string
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.NamedUser.NamedUser`
"""
... | python | def get_members(self, role=github.GithubObject.NotSet):
"""
:calls: `GET /teams/:id/members <https://developer.github.com/v3/teams/members/#list-team-members>`_
:param role: string
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.NamedUser.NamedUser`
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PyGithub/PyGithub | github/Team.py | Team.get_repos | def get_repos(self):
"""
:calls: `GET /teams/:id/repos <http://developer.github.com/v3/orgs/teams>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Repository.Repository`
"""
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github.Repository.Repositor... | python | def get_repos(self):
"""
:calls: `GET /teams/:id/repos <http://developer.github.com/v3/orgs/teams>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Repository.Repository`
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PyGithub/PyGithub | github/Team.py | Team.has_in_members | def has_in_members(self, member):
"""
:calls: `GET /teams/:id/members/:user <http://developer.github.com/v3/orgs/teams>`_
:param member: :class:`github.NamedUser.NamedUser`
:rtype: bool
"""
assert isinstance(member, github.NamedUser.NamedUser), member
status, head... | python | def has_in_members(self, member):
"""
:calls: `GET /teams/:id/members/:user <http://developer.github.com/v3/orgs/teams>`_
:param member: :class:`github.NamedUser.NamedUser`
:rtype: bool
"""
assert isinstance(member, github.NamedUser.NamedUser), member
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PyGithub/PyGithub | github/Team.py | Team.has_in_repos | def has_in_repos(self, repo):
"""
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:param repo: :class:`github.Repository.Repository`
:rtype: bool
"""
assert isinstance(repo, github.Repository.Repository), repo
status, heade... | python | def has_in_repos(self, repo):
"""
:calls: `GET /teams/:id/repos/:owner/:repo <http://developer.github.com/v3/orgs/teams>`_
:param repo: :class:`github.Repository.Repository`
:rtype: bool
"""
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PyGithub/PyGithub | github/Requester.py | Requester.NEW_DEBUG_FRAME | def NEW_DEBUG_FRAME(self, requestHeader):
"""
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"""
Initialize a debug frame with requestHeader
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if self.DEBUG_FLAG: # pragma no branch (Flag always set in tests)
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'''
Update current frame with response
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.as_issue | def as_issue(self):
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:calls: `GET /repos/:owner/:repo/issues/:number <http://developer.github.com/v3/issues>`_
:rtype: :class:`github.Issue.Issue`
"""
headers, data = self._requester.requestJsonAndCheck(
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"""
:calls: `GET /repos/:owner/:repo/issues/:number <http://developer.github.com/v3/issues>`_
:rtype: :class:`github.Issue.Issue`
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headers, data = self._requester.requestJsonAndCheck(
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.create_comment | def create_comment(self, body, commit_id, path, position):
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:param body: string
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:param path: string
:param positio... | python | def create_comment(self, body, commit_id, path, position):
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:calls: `POST /repos/:owner/:repo/pulls/:number/comments <http://developer.github.com/v3/pulls/comments>`_
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:param body: string
:param commit_id: :class:`github.Commit.Commit`
:param path: string
:param ... | python | def create_review_comment(self, body, commit_id, path, position):
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:calls: `POST /repos/:owner/:repo/pulls/:number/comments <http://developer.github.com/v3/pulls/comments>`_
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:rtype: :class:`github.IssueComment.IssueComment`
"""
assert isinstance(body, (str, unicode)), body
... | python | def create_issue_comment(self, body):
"""
:calls: `POST /repos/:owner/:repo/issues/:number/comments <http://developer.github.com/v3/issues/comments>`_
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.create_review | def create_review(self, commit=github.GithubObject.NotSet, body=None, event=github.GithubObject.NotSet, comments=github.GithubObject.NotSet):
"""
:calls: `POST /repos/:owner/:repo/pulls/:number/reviews <https://developer.github.com/v3/pulls/reviews/>`_
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"""
:calls: `POST /repos/:owner/:repo/pulls/:number/reviews <https://developer.github.com/v3/pulls/reviews/>`_
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.delete_review_request | def delete_review_request(self, reviewers=github.GithubObject.NotSet, team_reviewers=github.GithubObject.NotSet):
"""
:calls: `DELETE /repos/:owner/:repo/pulls/:number/requested_reviewers <https://developer.github.com/v3/pulls/review_requests/>`_
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:calls: `GET /repos/:owner/:repo/pulls/comments/:number <http://developer.github.com/v3/pulls/comments>`_
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:calls: `GET /repos/:owner/:repo/pulls/:number/comments <http://developer.github.com/v3/pulls/comments>`_
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"""
:calls: `GET /repos/:owner/:repo/pulls/:number/commits <http://developer.github.com/v3/pulls>`_
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"""
:calls: `GET /repos/:owner/:repo/pulls/:number/files <http://developer.github.com/v3/pulls>`_
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.get_issue_comment | def get_issue_comment(self, id):
"""
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:rtype: :class:`github.IssueComment.IssueComment`
"""
assert isinstance(id, (int, long)), id
headers, da... | python | def get_issue_comment(self, id):
"""
:calls: `GET /repos/:owner/:repo/issues/comments/:id <http://developer.github.com/v3/issues/comments>`_
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"""
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.get_review | def get_review(self, id):
"""
:calls: `GET /repos/:owner/:repo/pulls/:number/reviews/:id <https://developer.github.com/v3/pulls/reviews>`_
:param id: integer
:rtype: :class:`github.PullRequestReview.PullRequestReview`
"""
assert isinstance(id, (int, long)), id
hea... | python | def get_review(self, id):
"""
:calls: `GET /repos/:owner/:repo/pulls/:number/reviews/:id <https://developer.github.com/v3/pulls/reviews>`_
:param id: integer
:rtype: :class:`github.PullRequestReview.PullRequestReview`
"""
assert isinstance(id, (int, long)), id
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return github.PaginatedList.Paginate... | python | def get_reviews(self):
"""
:calls: `GET /repos/:owner/:repo/pulls/:number/reviews <https://developer.github.com/v3/pulls/reviews/>`_
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:rtype: tuple of :class:`github.PaginatedList.PaginatedList` of :class:`github.NamedUser.NamedUser` and of :class:`github.PaginatedList... | python | def get_review_requests(self):
"""
:calls: `GET /repos/:owner/:repo/pulls/:number/requested_reviewers <https://developer.github.com/v3/pulls/review_requests/>`_
:rtype: tuple of :class:`github.PaginatedList.PaginatedList` of :class:`github.NamedUser.NamedUser` and of :class:`github.PaginatedList... | [
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.get_labels | def get_labels(self):
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:calls: `GET /repos/:owner/:repo/issues/:number/labels <http://developer.github.com/v3/issues/labels>`_
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"""
:calls: `GET /repos/:owner/:repo/issues/:number/labels <http://developer.github.com/v3/issues/labels>`_
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.remove_from_labels | def remove_from_labels(self, label):
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:param label: :class:`github.Label.Label` or string
:rtype: None
"""
assert isinstance(label, (github.Label.Label, str... | python | def remove_from_labels(self, label):
"""
:calls: `DELETE /repos/:owner/:repo/issues/:number/labels/:name <http://developer.github.com/v3/issues/labels>`_
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"""
assert all(isinstance(element, (github.Label.Label, st... | python | def set_labels(self, *labels):
"""
:calls: `PUT /repos/:owner/:repo/issues/:number/labels <http://developer.github.com/v3/issues/labels>`_
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.is_merged | def is_merged(self):
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"""
:calls: `GET /repos/:owner/:repo/pulls/:number/merge <http://developer.github.com/v3/pulls>`_
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PyGithub/PyGithub | github/PullRequest.py | PullRequest.merge | def merge(self, commit_message=github.GithubObject.NotSet, commit_title=github.GithubObject.NotSet, merge_method=github.GithubObject.NotSet, sha=github.GithubObject.NotSet):
"""
:calls: `PUT /repos/:owner/:repo/pulls/:number/merge <http://developer.github.com/v3/pulls>`_
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:calls: `PUT /repos/:owner/:repo/pulls/:number/merge <http://developer.github.com/v3/pulls>`_
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"""
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self._completeIfNotSet(self._repository)
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# The repository was not set automatically, so it must be looked up by url.
repo_url = "/... | python | def repository(self):
"""
:type: :class:`github.Repository.Repository`
"""
self._completeIfNotSet(self._repository)
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repo_url = "/... | [
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PyGithub/PyGithub | github/Issue.py | Issue.as_pull_request | def as_pull_request(self):
"""
:calls: `GET /repos/:owner/:repo/pulls/:number <http://developer.github.com/v3/pulls>`_
:rtype: :class:`github.PullRequest.PullRequest`
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"""
:calls: `GET /repos/:owner/:repo/pulls/:number <http://developer.github.com/v3/pulls>`_
:rtype: :class:`github.PullRequest.PullRequest`
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PyGithub/PyGithub | github/Issue.py | Issue.add_to_assignees | def add_to_assignees(self, *assignees):
"""
:calls: `POST /repos/:owner/:repo/issues/:number/assignees <https://developer.github.com/v3/issues/assignees>`_
:param assignee: :class:`github.NamedUser.NamedUser` or string
:rtype: None
"""
assert all(isinstance(element, (gith... | python | def add_to_assignees(self, *assignees):
"""
:calls: `POST /repos/:owner/:repo/issues/:number/assignees <https://developer.github.com/v3/issues/assignees>`_
:param assignee: :class:`github.NamedUser.NamedUser` or string
:rtype: None
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PyGithub/PyGithub | github/Issue.py | Issue.create_comment | def create_comment(self, body):
"""
:calls: `POST /repos/:owner/:repo/issues/:number/comments <http://developer.github.com/v3/issues/comments>`_
:param body: string
:rtype: :class:`github.IssueComment.IssueComment`
"""
assert isinstance(body, (str, unicode)), body
... | python | def create_comment(self, body):
"""
:calls: `POST /repos/:owner/:repo/issues/:number/comments <http://developer.github.com/v3/issues/comments>`_
:param body: string
:rtype: :class:`github.IssueComment.IssueComment`
"""
assert isinstance(body, (str, unicode)), body
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PyGithub/PyGithub | github/Issue.py | Issue.edit | def edit(self, title=github.GithubObject.NotSet, body=github.GithubObject.NotSet, assignee=github.GithubObject.NotSet, state=github.GithubObject.NotSet, milestone=github.GithubObject.NotSet, labels=github.GithubObject.NotSet, assignees=github.GithubObject.NotSet):
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:calls: `PATCH /repos/:owner/:repo/... | python | def edit(self, title=github.GithubObject.NotSet, body=github.GithubObject.NotSet, assignee=github.GithubObject.NotSet, state=github.GithubObject.NotSet, milestone=github.GithubObject.NotSet, labels=github.GithubObject.NotSet, assignees=github.GithubObject.NotSet):
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PyGithub/PyGithub | github/Issue.py | Issue.get_comments | def get_comments(self, since=github.GithubObject.NotSet):
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:calls: `GET /repos/:owner/:repo/issues/:number/comments <http://developer.github.com/v3/issues/comments>`_
:param since: datetime.datetime format YYYY-MM-DDTHH:MM:SSZ
:rtype: :class:`github.PaginatedList.PaginatedList` of :cl... | python | def get_comments(self, since=github.GithubObject.NotSet):
"""
:calls: `GET /repos/:owner/:repo/issues/:number/comments <http://developer.github.com/v3/issues/comments>`_
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"""
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"""
return github.PaginatedList.PaginatedList(
... | python | def get_events(self):
"""
:calls: `GET /repos/:owner/:repo/issues/:issue_number/events <http://developer.github.com/v3/issues/events>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.IssueEvent.IssueEvent`
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return github.PaginatedList.PaginatedList(
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PyGithub/PyGithub | github/Issue.py | Issue.get_labels | def get_labels(self):
"""
:calls: `GET /repos/:owner/:repo/issues/:number/labels <http://developer.github.com/v3/issues/labels>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Label.Label`
"""
return github.PaginatedList.PaginatedList(
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"""
:calls: `GET /repos/:owner/:repo/issues/:number/labels <http://developer.github.com/v3/issues/labels>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Label.Label`
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PyGithub/PyGithub | github/Issue.py | Issue.get_reactions | def get_reactions(self):
"""
:calls: `GET /repos/:owner/:repo/issues/:number/reactions <https://developer.github.com/v3/reactions/#list-reactions-for-an-issue>`_
:return: :class: :class:`github.PaginatedList.PaginatedList` of :class:`github.Reaction.Reaction`
"""
return github.Pa... | python | def get_reactions(self):
"""
:calls: `GET /repos/:owner/:repo/issues/:number/reactions <https://developer.github.com/v3/reactions/#list-reactions-for-an-issue>`_
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PyGithub/PyGithub | github/Issue.py | Issue.create_reaction | def create_reaction(self, reaction_type):
"""
:calls: `POST /repos/:owner/:repo/issues/:number/reactions <https://developer.github.com/v3/reactions>`_
:param reaction_type: string
:rtype: :class:`github.Reaction.Reaction`
"""
assert isinstance(reaction_type, (str, unicode... | python | def create_reaction(self, reaction_type):
"""
:calls: `POST /repos/:owner/:repo/issues/:number/reactions <https://developer.github.com/v3/reactions>`_
:param reaction_type: string
:rtype: :class:`github.Reaction.Reaction`
"""
assert isinstance(reaction_type, (str, unicode... | [
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PyGithub/PyGithub | github/Milestone.py | Milestone.edit | def edit(self, title, state=github.GithubObject.NotSet, description=github.GithubObject.NotSet, due_on=github.GithubObject.NotSet):
"""
:calls: `PATCH /repos/:owner/:repo/milestones/:number <http://developer.github.com/v3/issues/milestones>`_
:param title: string
:param state: string
... | python | def edit(self, title, state=github.GithubObject.NotSet, description=github.GithubObject.NotSet, due_on=github.GithubObject.NotSet):
"""
:calls: `PATCH /repos/:owner/:repo/milestones/:number <http://developer.github.com/v3/issues/milestones>`_
:param title: string
:param state: string
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PyGithub/PyGithub | github/Organization.py | Organization.add_to_public_members | def add_to_public_members(self, public_member):
"""
:calls: `PUT /orgs/:org/public_members/:user <http://developer.github.com/v3/orgs/members>`_
:param public_member: :class:`github.NamedUser.NamedUser`
:rtype: None
"""
assert isinstance(public_member, github.NamedUser.Na... | python | def add_to_public_members(self, public_member):
"""
:calls: `PUT /orgs/:org/public_members/:user <http://developer.github.com/v3/orgs/members>`_
:param public_member: :class:`github.NamedUser.NamedUser`
:rtype: None
"""
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PyGithub/PyGithub | github/Organization.py | Organization.create_fork | def create_fork(self, repo):
"""
:calls: `POST /repos/:owner/:repo/forks <http://developer.github.com/v3/repos/forks>`_
:param repo: :class:`github.Repository.Repository`
:rtype: :class:`github.Repository.Repository`
"""
assert isinstance(repo, github.Repository.Repositor... | python | def create_fork(self, repo):
"""
:calls: `POST /repos/:owner/:repo/forks <http://developer.github.com/v3/repos/forks>`_
:param repo: :class:`github.Repository.Repository`
:rtype: :class:`github.Repository.Repository`
"""
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PyGithub/PyGithub | github/Organization.py | Organization.create_hook | def create_hook(self, name, config, events=github.GithubObject.NotSet, active=github.GithubObject.NotSet):
"""
:calls: `POST /orgs/:owner/hooks <http://developer.github.com/v3/orgs/hooks>`_
:param name: string
:param config: dict
:param events: list of string
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"""
:calls: `POST /orgs/:owner/hooks <http://developer.github.com/v3/orgs/hooks>`_
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PyGithub/PyGithub | github/Organization.py | Organization.create_team | def create_team(self, name, repo_names=github.GithubObject.NotSet, permission=github.GithubObject.NotSet, privacy=github.GithubObject.NotSet):
"""
:calls: `POST /orgs/:org/teams <http://developer.github.com/v3/orgs/teams>`_
:param name: string
:param repo_names: list of :class:`github.Re... | python | def create_team(self, name, repo_names=github.GithubObject.NotSet, permission=github.GithubObject.NotSet, privacy=github.GithubObject.NotSet):
"""
:calls: `POST /orgs/:org/teams <http://developer.github.com/v3/orgs/teams>`_
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PyGithub/PyGithub | github/Organization.py | Organization.delete_hook | def delete_hook(self, id):
"""
:calls: `DELETE /orgs/:owner/hooks/:id <http://developer.github.com/v3/orgs/hooks>`_
:param id: integer
:rtype: None`
"""
assert isinstance(id, (int, long)), id
headers, data = self._requester.requestJsonAndCheck(
"DELETE... | python | def delete_hook(self, id):
"""
:calls: `DELETE /orgs/:owner/hooks/:id <http://developer.github.com/v3/orgs/hooks>`_
:param id: integer
:rtype: None`
"""
assert isinstance(id, (int, long)), id
headers, data = self._requester.requestJsonAndCheck(
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PyGithub/PyGithub | github/Organization.py | Organization.edit | def edit(self, billing_email=github.GithubObject.NotSet, blog=github.GithubObject.NotSet, company=github.GithubObject.NotSet, description=github.GithubObject.NotSet, email=github.GithubObject.NotSet, location=github.GithubObject.NotSet, name=github.GithubObject.NotSet):
"""
:calls: `PATCH /orgs/:org <ht... | python | def edit(self, billing_email=github.GithubObject.NotSet, blog=github.GithubObject.NotSet, company=github.GithubObject.NotSet, description=github.GithubObject.NotSet, email=github.GithubObject.NotSet, location=github.GithubObject.NotSet, name=github.GithubObject.NotSet):
"""
:calls: `PATCH /orgs/:org <ht... | [
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PyGithub/PyGithub | github/Organization.py | Organization.get_events | def get_events(self):
"""
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:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Event.Event`
"""
return github.PaginatedList.PaginatedList(
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... | python | def get_events(self):
"""
:calls: `GET /orgs/:org/events <http://developer.github.com/v3/activity/events>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Event.Event`
"""
return github.PaginatedList.PaginatedList(
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PyGithub/PyGithub | github/Organization.py | Organization.get_hook | def get_hook(self, id):
"""
:calls: `GET /orgs/:owner/hooks/:id <http://developer.github.com/v3/orgs/hooks>`_
:param id: integer
:rtype: :class:`github.Hook.Hook`
"""
assert isinstance(id, (int, long)), id
headers, data = self._requester.requestJsonAndCheck(
... | python | def get_hook(self, id):
"""
:calls: `GET /orgs/:owner/hooks/:id <http://developer.github.com/v3/orgs/hooks>`_
:param id: integer
:rtype: :class:`github.Hook.Hook`
"""
assert isinstance(id, (int, long)), id
headers, data = self._requester.requestJsonAndCheck(
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"""
:calls: `GET /orgs/:owner/hooks <http://developer.github.com/v3/orgs/hooks>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Hook.Hook`
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return github.PaginatedList.PaginatedList(
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self._r... | python | def get_hooks(self):
"""
:calls: `GET /orgs/:owner/hooks <http://developer.github.com/v3/orgs/hooks>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Hook.Hook`
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PyGithub/PyGithub | github/Organization.py | Organization.get_members | def get_members(self, filter_=github.GithubObject.NotSet,
role=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/members <http://developer.github.com/v3/orgs/members>`_
:param filter_: string
:param role: string
:rtype: :class:`github.PaginatedList.Pagi... | python | def get_members(self, filter_=github.GithubObject.NotSet,
role=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/members <http://developer.github.com/v3/orgs/members>`_
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PyGithub/PyGithub | github/Organization.py | Organization.get_projects | def get_projects(self, state=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/projects <https://developer.github.com/v3/projects/#list-organization-projects>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Project.Project`
:param state: string
"""
... | python | def get_projects(self, state=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/projects <https://developer.github.com/v3/projects/#list-organization-projects>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Project.Project`
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PyGithub/PyGithub | github/Organization.py | Organization.get_public_members | def get_public_members(self):
"""
:calls: `GET /orgs/:org/public_members <http://developer.github.com/v3/orgs/members>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.NamedUser.NamedUser`
"""
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"""
:calls: `GET /orgs/:org/public_members <http://developer.github.com/v3/orgs/members>`_
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.NamedUser.NamedUser`
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PyGithub/PyGithub | github/Organization.py | Organization.get_outside_collaborators | def get_outside_collaborators(self, filter_=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/outside_collaborators <http://developer.github.com/v3/orgs/outside_collaborators>`_
:param filter_: string
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.NamedUser.... | python | def get_outside_collaborators(self, filter_=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/outside_collaborators <http://developer.github.com/v3/orgs/outside_collaborators>`_
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PyGithub/PyGithub | github/Organization.py | Organization.remove_outside_collaborator | def remove_outside_collaborator(self, collaborator):
"""
:calls: `DELETE /orgs/:org/outside_collaborators/:username <https://developer.github.com/v3/orgs/outside_collaborators>`_
:param collaborator: :class:`github.NamedUser.NamedUser`
:rtype: None
"""
assert isinstance(c... | python | def remove_outside_collaborator(self, collaborator):
"""
:calls: `DELETE /orgs/:org/outside_collaborators/:username <https://developer.github.com/v3/orgs/outside_collaborators>`_
:param collaborator: :class:`github.NamedUser.NamedUser`
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"""
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PyGithub/PyGithub | github/Organization.py | Organization.convert_to_outside_collaborator | def convert_to_outside_collaborator(self, member):
"""
:calls: `PUT /orgs/:org/outside_collaborators/:username <https://developer.github.com/v3/orgs/outside_collaborators>`_
:param member: :class:`github.NamedUser.NamedUser`
:rtype: None
"""
assert isinstance(member, gith... | python | def convert_to_outside_collaborator(self, member):
"""
:calls: `PUT /orgs/:org/outside_collaborators/:username <https://developer.github.com/v3/orgs/outside_collaborators>`_
:param member: :class:`github.NamedUser.NamedUser`
:rtype: None
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"memb... | f716df86bbe7dc276c6596699fa9712b61ef974c | https://github.com/PyGithub/PyGithub/blob/f716df86bbe7dc276c6596699fa9712b61ef974c/github/Organization.py#L734-L744 | train | Converts a user to the outside Collaborator. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
PyGithub/PyGithub | github/Organization.py | Organization.get_repo | def get_repo(self, name):
"""
:calls: `GET /repos/:owner/:repo <http://developer.github.com/v3/repos>`_
:param name: string
:rtype: :class:`github.Repository.Repository`
"""
assert isinstance(name, (str, unicode)), name
headers, data = self._requester.requestJsonA... | python | def get_repo(self, name):
"""
:calls: `GET /repos/:owner/:repo <http://developer.github.com/v3/repos>`_
:param name: string
:rtype: :class:`github.Repository.Repository`
"""
assert isinstance(name, (str, unicode)), name
headers, data = self._requester.requestJsonA... | [
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PyGithub/PyGithub | github/Organization.py | Organization.get_repos | def get_repos(self, type=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/repos <http://developer.github.com/v3/repos>`_
:param type: string ('all', 'public', 'private', 'forks', 'sources', 'member')
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Repository... | python | def get_repos(self, type=github.GithubObject.NotSet):
"""
:calls: `GET /orgs/:org/repos <http://developer.github.com/v3/repos>`_
:param type: string ('all', 'public', 'private', 'forks', 'sources', 'member')
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Repository... | [
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:param type: string ('all', 'public', 'private', 'forks', 'sources', 'member')
:rtype: :class:`github.PaginatedList.PaginatedList` of :class:`github.Repository.Repository` | [
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