Masking: remove flakiness from test (#31939)
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@@ -1571,9 +1571,6 @@ class WhisperModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
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out_last_tokens = logits[:, -1, :] # last tokens in each batch line
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out_last_tokens = logits[:, -1, :] # last tokens in each batch line
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out_shared_prefix_last_tokens = logits_shared_prefix[0, -3:, :] # last three tokens
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out_shared_prefix_last_tokens = logits_shared_prefix[0, -3:, :] # last three tokens
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# comparing greedily-chosen tokens:
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assert torch.equal(out_last_tokens.max(axis=1).indices, out_shared_prefix_last_tokens.max(axis=1).indices)
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# comparing softmax-normalized logits:
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# comparing softmax-normalized logits:
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normalized_0 = torch.nn.functional.softmax(out_last_tokens)
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normalized_0 = torch.nn.functional.softmax(out_last_tokens)
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normalized_1 = torch.nn.functional.softmax(out_shared_prefix_last_tokens)
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normalized_1 = torch.nn.functional.softmax(out_shared_prefix_last_tokens)
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@@ -4486,9 +4486,6 @@ class ModelTesterMixin:
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out_last_tokens = logits[:, -1, :] # last tokens in each batch line
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out_last_tokens = logits[:, -1, :] # last tokens in each batch line
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out_shared_prefix_last_tokens = logits_shared_prefix[0, -3:, :] # last three tokens
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out_shared_prefix_last_tokens = logits_shared_prefix[0, -3:, :] # last three tokens
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# comparing greedily-chosen tokens:
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assert torch.equal(out_last_tokens.max(axis=1).indices, out_shared_prefix_last_tokens.max(axis=1).indices)
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# comparing softmax-normalized logits:
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# comparing softmax-normalized logits:
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normalized_0 = F.softmax(out_last_tokens)
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normalized_0 = F.softmax(out_last_tokens)
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normalized_1 = F.softmax(out_shared_prefix_last_tokens)
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normalized_1 = F.softmax(out_shared_prefix_last_tokens)
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