mirror of https://github.com/hpcaitech/ColossalAI
diverse tests
parent
1821a6dab0
commit
ae24b4f025
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@ -117,7 +117,8 @@ class InferenceEngine:
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max_context_len_to_capture = self.inference_config.max_context_len_to_capture
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max_num_blocks = (max_context_len_to_capture + block_size - 1) // block_size
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input_tokens_ids = torch.zeros(max_batch_size, dtype=torch.long).cuda()
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self.graph_block_tables = np.zeros((max(_BATCH_SIZES_TO_CAPTURE), max_num_blocks), dtype=np.int32)
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# self.graph_block_tables = np.zeros((max(_BATCH_SIZES_TO_CAPTURE), max_num_blocks), dtype=np.int32)
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self.graph_block_tables = np.full((max(_BATCH_SIZES_TO_CAPTURE), max_num_blocks), -1, dtype=np.int32)
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self.graph_block_tables[:, 0] = np.arange(max_num_blocks, max_num_blocks + max(_BATCH_SIZES_TO_CAPTURE))
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self.graph_block_tables[0, :] = np.arange(
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0, max_num_blocks
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@ -34,7 +34,9 @@ def check_inference_engine(use_cuda_graph=False, batch_size=32):
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prompts_token_ids = []
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for i in range(batch_size):
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prompts_token_ids.append(np.random.randint(low=0, high=100, size=random.randint(1, 1024)).tolist())
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prompts_token_ids.append(
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np.random.randint(low=0, high=100, size=random.randint(1, max(1024 // batch_size, 32))).tolist()
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)
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input_len = 1024
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output_len = 128
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