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Ignore some pytype errors. #1197

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Ignore some pytype errors. #1197

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2 changes: 1 addition & 1 deletion scenic/model_lib/base_models/classification_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@
})


def classification_metrics_function(
def classification_metrics_function( # pytype: disable=annotation-type-mismatch
logits: jnp.ndarray,
batch: base_model.Batch,
target_is_onehot: bool = False,
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2 changes: 1 addition & 1 deletion scenic/model_lib/base_models/encoder_decoder_model.py
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Expand Up @@ -61,7 +61,7 @@ def num_tokens(logits: jnp.ndarray,
_MAX_PERPLEXITY = 1.0e4


def encoder_decoder_metrics_function(
def encoder_decoder_metrics_function( # pytype: disable=annotation-type-mismatch
logits: jnp.ndarray,
batch: base_model.Batch,
target_is_onehot: bool = False,
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2 changes: 1 addition & 1 deletion scenic/model_lib/base_models/multilabel_classification_model.py
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Expand Up @@ -37,7 +37,7 @@ def multilabel_classification_metrics_function(
logits: jnp.ndarray,
batch: base_model.Batch,
target_is_multihot: bool = False,
metrics: base_model.MetricNormalizerFnDict = _MULTI_LABEL_CLASSIFICATION_METRICS,
metrics: base_model.MetricNormalizerFnDict = _MULTI_LABEL_CLASSIFICATION_METRICS, # pytype: disable=annotation-type-mismatch
axis_name: Union[str, Tuple[str, ...]] = 'batch',
) -> Dict[str, Tuple[float, int]]:
"""Calculates metrics for the multi-label classification task.
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2 changes: 1 addition & 1 deletion scenic/model_lib/base_models/regression_model.py
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Expand Up @@ -29,7 +29,7 @@
})


def regression_metrics_function(
def regression_metrics_function( # pytype: disable=annotation-type-mismatch
predictions: jnp.ndarray,
batch: base_model.Batch,
metrics: base_model.MetricNormalizerFnDict = _REGRESSION_METRICS,
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2 changes: 1 addition & 1 deletion scenic/model_lib/base_models/segmentation_model.py
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Expand Up @@ -61,7 +61,7 @@ def num_pixels(logits: jnp.ndarray,
})


def semantic_segmentation_metrics_function(
def semantic_segmentation_metrics_function( # pytype: disable=annotation-type-mismatch
logits: jnp.ndarray,
batch: base_model.Batch,
target_is_onehot: bool = False,
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2 changes: 1 addition & 1 deletion scenic/projects/av_mae/base_model.py
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Expand Up @@ -194,7 +194,7 @@ def get_spectogram_targets(inputs: jnp.ndarray,
return patched_input


def feature_regression_metrics_function(
def feature_regression_metrics_function( # pytype: disable=annotation-type-mismatch
predictions: jnp.ndarray,
prediction_masks: jnp.ndarray,
batch: base_model.Batch,
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6 changes: 3 additions & 3 deletions scenic/projects/polyvit/polyvit_base_model.py
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Expand Up @@ -66,7 +66,7 @@ class Modality:
})


def bow_classification_metrics_function(
def bow_classification_metrics_function( # pytype: disable=annotation-type-mismatch
logits: jnp.ndarray,
batch: base_model.Batch,
target_is_multihot: bool = False,
Expand Down Expand Up @@ -120,7 +120,7 @@ def bow_classification_metrics_function(
return evaluated_metrics # pytype: disable=bad-return-type # jax-types


def multihead_classification_metrics_function(
def multihead_classification_metrics_function( # pytype: disable=annotation-type-mismatch
logits,
batch,
metrics: base_model.MetricNormalizerFnDict = _MULTIHEADLABEL_METRICS,
Expand Down Expand Up @@ -183,7 +183,7 @@ def multihead_classification_metrics_function(

def classification_metrics_function_with_acc_top_5(*args, **kwargs):
"""A wrapper over classification_metrics_function which has accuracy_top_5."""
return classification_metrics_function(
return classification_metrics_function( # pytype: disable=wrong-arg-types
*args, metrics=_MULTIHEADLABEL_METRICS, **kwargs)


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