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set the dtype to float32 during tokenization when no padding is needed #65

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Merged
iLampard merged 1 commit into from
Apr 9, 2025
Merged

set the dtype to float32 during tokenization when no padding is needed #65

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6 changes: 3 additions & 3 deletions easy_tpp/preprocess/event_tokenizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -414,9 +414,9 @@ def _pad(
max_len=max_length,
dtype=np.int64)
else:
batch_output[self.model_input_names[0]] = np.array(encoded_inputs[self.model_input_names[0]])
batch_output[self.model_input_names[1]] = np.array(encoded_inputs[self.model_input_names[1]])
batch_output[self.model_input_names[2]] = np.array(encoded_inputs[self.model_input_names[2]])
batch_output[self.model_input_names[0]] = np.array(encoded_inputs[self.model_input_names[0]], dtype=np.float32)
batch_output[self.model_input_names[1]] = np.array(encoded_inputs[self.model_input_names[1]], dtype=np.float32)
batch_output[self.model_input_names[2]] = np.array(encoded_inputs[self.model_input_names[2]], dtype=np.int64)

# non_pad_mask; replaced the use of event types by using the original sequence length
seq_pad_mask = np.full_like(batch_output[self.model_input_names[2]], fill_value=True, dtype=bool)
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