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naming
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@ -39,7 +39,7 @@ def get_docs():
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def test_components_batching_list(name):
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nlp = English()
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proc = nlp.create_pipe(name)
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util_batch_unbatch_List(proc.model, get_docs(), list_floats)
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util_batch_unbatch_docs_list(proc.model, get_docs(), list_floats)
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# Test components with a model of type Model[List[Doc], Floats2d]
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@ -48,7 +48,7 @@ def test_components_batching_array(name):
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nlp = English()
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in_data = [nlp(text) for text in texts]
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proc = nlp.create_pipe(name)
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util_batch_unbatch_Array(proc.model, get_docs(), array)
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util_batch_unbatch_docs_array(proc.model, get_docs(), array)
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LAYERS = [
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@ -63,19 +63,19 @@ def test_layers_batching_all(model, in_data, out_data):
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# In = List[Doc]
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if isinstance(in_data, list) and isinstance(in_data[0], Doc):
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if isinstance(out_data, OPS.xp.ndarray) and out_data.ndim == 2:
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util_batch_unbatch_Array(model, in_data, out_data)
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util_batch_unbatch_docs_array(model, in_data, out_data)
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elif (
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isinstance(out_data, list)
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and isinstance(out_data[0], OPS.xp.ndarray)
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and out_data[0].ndim == 2
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):
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util_batch_unbatch_List(model, in_data, out_data)
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util_batch_unbatch_docs_list(model, in_data, out_data)
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elif isinstance(out_data, Ragged):
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util_batch_unbatch_Ragged(model, in_data, out_data)
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util_batch_unbatch_docs_ragged(model, in_data, out_data)
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def util_batch_unbatch_List(
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def util_batch_unbatch_docs_list(
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model: Model[List[Doc], List[Array2d]], in_data: List[Doc], out_data: List[Array2d]
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):
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with data_validation(True):
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@ -86,7 +86,7 @@ def util_batch_unbatch_List(
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assert_almost_equal(Y_batched[i], Y_not_batched[i], decimal=4)
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def util_batch_unbatch_Array(
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def util_batch_unbatch_docs_array(
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model: Model[List[Doc], Array2d], in_data: List[Doc], out_data: Array2d
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):
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with data_validation(True):
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@ -96,7 +96,7 @@ def util_batch_unbatch_Array(
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assert_almost_equal(Y_batched, Y_not_batched, decimal=4)
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def util_batch_unbatch_Ragged(
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def util_batch_unbatch_docs_ragged(
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model: Model[List[Doc], Ragged], in_data: List[Doc], out_data: Ragged
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):
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with data_validation(True):
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