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Added type hinting and code formatting.

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Isabelle 2023-05-04 16:48:56 +03:00 committed by GitHub
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commit 68351724e9
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1 changed files with 14 additions and 8 deletions
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22
src/python/twitter/deepbird/projects/timelines/scripts/models/earlybird/example_weights.py
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@ -1,9 +1,12 @@
# checkstyle: noqa # checkstyle: noqa
from typing import Dict, Final
from tensorflow import Tensor
from twml import DefaultSubcommandArgParse
import tensorflow.compat.v1 as tf import tensorflow.compat.v1 as tf
from .constants import INDEX_BY_LABEL, LABEL_NAMES from .constants import INDEX_BY_LABEL, LABEL_NAMES
# TODO: Read these from command line arguments, since they specify the existing example weights in the input data. # TODO: Read these from command line arguments, since they specify the existing example weights in the input data.
DEFAULT_WEIGHT_BY_LABEL = { DEFAULT_WEIGHT_BY_LABEL: Final[Dict[str, float]] = {
"is_clicked": 0.3, "is_clicked": 0.3,
"is_favorited": 1.0, "is_favorited": 1.0,
"is_open_linked": 0.1, "is_open_linked": 0.1,
@ -11,19 +14,19 @@ DEFAULT_WEIGHT_BY_LABEL = {
"is_profile_clicked": 1.0, "is_profile_clicked": 1.0,
"is_replied": 9.0, "is_replied": 9.0,
"is_retweeted": 1.0, "is_retweeted": 1.0,
"is_video_playback_50": 0.01 "is_video_playback_50": 0.01,
} }
def add_weight_arguments(parser): def add_weight_arguments(parser: DefaultSubcommandArgParse) -> DefaultSubcommandArgParse:
for label_name in LABEL_NAMES: for label_name in LABEL_NAMES:
parser.add_argument( parser.add_argument(
_make_weight_cli_argument_name(label_name), _make_weight_cli_argument_name(label_name),
type=float, type=float,
default=DEFAULT_WEIGHT_BY_LABEL[label_name], default=DEFAULT_WEIGHT_BY_LABEL[label_name],
dest=_make_weight_param_name(label_name) dest=_make_weight_param_name(label_name),
) )
def make_weights_tensor(input_weights, label, params): def make_weights_tensor(input_weights, label, params) -> Tensor:
''' '''
Replaces the weights for each positive engagement and keeps the input weights for negative examples. Replaces the weights for each positive engagement and keeps the input weights for negative examples.
''' '''
@ -32,12 +35,15 @@ def make_weights_tensor(input_weights, label, params):
index, default_weight = INDEX_BY_LABEL[label_name], DEFAULT_WEIGHT_BY_LABEL[label_name] index, default_weight = INDEX_BY_LABEL[label_name], DEFAULT_WEIGHT_BY_LABEL[label_name]
weight_param_name =_make_weight_param_name(label_name) weight_param_name =_make_weight_param_name(label_name)
weight_tensors.append( weight_tensors.append(
tf.reshape(tf.math.scalar_mul(getattr(params, weight_param_name) - default_weight, label[:, index]), [-1, 1]) tf.reshape(
tf.math.scalar_mul(
getattr(params, weight_param_name) - default_weight, label[:, index]
), [-1, 1])
) )
return tf.math.accumulate_n(weight_tensors) return tf.math.accumulate_n(weight_tensors)
def _make_weight_cli_argument_name(label_name): def _make_weight_cli_argument_name(label_name: str) -> str:
return f"--weight.{label_name}" return f"--weight.{label_name}"
def _make_weight_param_name(label_name): def _make_weight_param_name(label_name: str) -> str:
return f"weight_{label_name}" return f"weight_{label_name}"