mirror of
https://github.com/zebrajr/tensorflow.git
synced 2025-12-06 12:20:11 +01:00
Introduce PyMetric as an experimental Keras API.
PiperOrigin-RevId: 508696238
This commit is contained in:
A. Unique TensorFlower
TensorFlower Gardener
parent
66c959717c
commit
08c9c1d88f
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@ -22,6 +22,11 @@
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* Added F-Score metrics `tf.keras.metrics.FBetaScore`,
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`tf.keras.metrics.F1Score`, and `tf.keras.metrics.R2Score`.
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* Added activation function `tf.keras.activations.mish`.
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* Added experimental `keras.metrics.experimental.PyMetric` API for metrics
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that run Python code on the host CPU (compiled outside of the TensorFlow
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graph). This can be used for integrating metrics from external Python
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libraries (like sklearn or pycocotools) into Keras as first-class Keras
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metrics.
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# Bug Fixes and Other Changes
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@ -0,0 +1,255 @@
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path: "tensorflow.metrics.experimental.PyMetric"
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tf_class {
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is_instance: "<class \'keras.metrics.py_metric.PyMetric\'>"
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is_instance: "<class \'keras.metrics.base_metric.Metric\'>"
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is_instance: "<class \'keras.engine.base_layer.Layer\'>"
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is_instance: "<class \'tensorflow.python.module.module.Module\'>"
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is_instance: "<class \'tensorflow.python.trackable.autotrackable.AutoTrackable\'>"
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is_instance: "<class \'tensorflow.python.trackable.base.Trackable\'>"
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is_instance: "<class \'keras.utils.version_utils.LayerVersionSelector\'>"
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is_instance: "<type \'object\'>"
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member {
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name: "activity_regularizer"
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mtype: "<type \'property\'>"
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}
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member {
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name: "compute_dtype"
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mtype: "<type \'property\'>"
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}
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member {
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name: "dtype"
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mtype: "<type \'property\'>"
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}
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member {
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name: "dtype_policy"
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mtype: "<type \'property\'>"
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}
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member {
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name: "dynamic"
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mtype: "<type \'property\'>"
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}
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member {
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name: "inbound_nodes"
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mtype: "<type \'property\'>"
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}
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member {
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name: "input"
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mtype: "<type \'property\'>"
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}
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member {
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name: "input_mask"
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mtype: "<type \'property\'>"
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}
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member {
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name: "input_shape"
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mtype: "<type \'property\'>"
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}
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member {
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name: "input_spec"
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mtype: "<type \'property\'>"
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}
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member {
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name: "losses"
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mtype: "<type \'property\'>"
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}
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member {
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name: "metrics"
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mtype: "<type \'property\'>"
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}
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member {
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name: "name"
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mtype: "<type \'property\'>"
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}
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member {
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name: "name_scope"
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mtype: "<type \'property\'>"
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}
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member {
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name: "non_trainable_variables"
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mtype: "<type \'property\'>"
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}
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member {
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name: "non_trainable_weights"
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mtype: "<type \'property\'>"
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}
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member {
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name: "outbound_nodes"
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mtype: "<type \'property\'>"
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}
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member {
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name: "output"
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mtype: "<type \'property\'>"
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}
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member {
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name: "output_mask"
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mtype: "<type \'property\'>"
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}
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member {
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name: "output_shape"
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mtype: "<type \'property\'>"
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}
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member {
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name: "stateful"
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mtype: "<type \'property\'>"
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}
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member {
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name: "submodules"
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mtype: "<type \'property\'>"
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}
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member {
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name: "supports_masking"
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mtype: "<type \'property\'>"
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}
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member {
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name: "trainable"
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mtype: "<type \'property\'>"
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}
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member {
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name: "trainable_variables"
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mtype: "<type \'property\'>"
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}
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member {
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name: "trainable_weights"
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mtype: "<type \'property\'>"
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}
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member {
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name: "updates"
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mtype: "<type \'property\'>"
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}
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member {
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name: "variable_dtype"
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mtype: "<type \'property\'>"
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}
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member {
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name: "variables"
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mtype: "<type \'property\'>"
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}
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member {
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name: "weights"
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mtype: "<type \'property\'>"
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}
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member_method {
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name: "__init__"
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argspec: "args=[\'self\', \'name\', \'dtype\'], varargs=None, keywords=kwargs, defaults=[\'None\', \'None\'], "
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}
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member_method {
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name: "add_loss"
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argspec: "args=[\'self\', \'losses\'], varargs=None, keywords=kwargs, defaults=None"
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}
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member_method {
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name: "add_metric"
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argspec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=kwargs, defaults=[\'None\'], "
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}
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member_method {
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name: "add_update"
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argspec: "args=[\'self\', \'updates\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "add_variable"
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argspec: "args=[\'self\'], varargs=args, keywords=kwargs, defaults=None"
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}
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member_method {
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name: "add_weight"
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argspec: "args=[\'self\', \'name\', \'shape\', \'aggregation\', \'synchronization\', \'initializer\', \'dtype\'], varargs=None, keywords=None, defaults=[\'()\', \'VariableAggregationV2.SUM\', \'VariableSynchronization.ON_READ\', \'None\', \'None\'], "
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}
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member_method {
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name: "build"
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argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "build_from_config"
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argspec: "args=[\'self\', \'config\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "call"
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argspec: "args=[\'self\', \'inputs\'], varargs=args, keywords=kwargs, defaults=None"
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}
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member_method {
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name: "compute_mask"
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argspec: "args=[\'self\', \'inputs\', \'mask\'], varargs=None, keywords=None, defaults=[\'None\'], "
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}
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member_method {
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name: "compute_output_shape"
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argspec: "args=[\'self\', \'input_shape\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "compute_output_signature"
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argspec: "args=[\'self\', \'input_signature\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "count_params"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "finalize_state"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "from_config"
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argspec: "args=[\'cls\', \'config\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_build_config"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_config"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_input_at"
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argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_input_mask_at"
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argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_input_shape_at"
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argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_output_at"
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argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_output_mask_at"
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argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_output_shape_at"
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argspec: "args=[\'self\', \'node_index\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "get_weights"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "merge_state"
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argspec: "args=[\'self\', \'metrics\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "reset_state"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "reset_states"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "result"
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argspec: "args=[\'self\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "set_weights"
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argspec: "args=[\'self\', \'weights\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "update_state"
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argspec: "args=[\'self\', \'y_true\', \'y_pred\', \'sample_weight\'], varargs=None, keywords=None, defaults=[\'None\'], "
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}
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member_method {
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name: "with_name_scope"
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argspec: "args=[\'cls\', \'method\'], varargs=None, keywords=None, defaults=None"
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}
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}
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@ -0,0 +1,7 @@
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path: "tensorflow.metrics.experimental"
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tf_module {
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member {
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name: "PyMetric"
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mtype: "<type \'type\'>"
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}
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}
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