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https://github.com/NVIDIA/TensorRT-LLM.git
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deaae40bd7
* Update TensorRT-LLM --------- Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
75 lines
2.5 KiB
Python
Executable File
75 lines
2.5 KiB
Python
Executable File
#!/usr/bin/env python3
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# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import csv
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import os
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import numpy as np
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def csv_to_npy(input_file, output_file, pad_id, verbose):
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data = []
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with open(input_file, newline='') as csvfile:
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csv_reader = csv.reader(csvfile, delimiter=',')
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for line in csv_reader:
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data.append([int(e) for e in line])
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max_input_length = max([len(x) for x in data])
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data = [row + [pad_id] * (max_input_length - len(row)) for row in data]
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data = np.array(data, dtype='int32')
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if (verbose):
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print(data, data.dtype)
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np.save(output_file, data)
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def npy_to_csv(input_file, output_file, verbose):
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data = np.load(input_file)
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if (verbose):
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print(data, data.dtype)
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np.savetxt(output_file, data, delimiter=",", fmt='%i')
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'input_file',
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type=str,
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help='Read token ids from this file. Must be csv or npy.')
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parser.add_argument('output_file',
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type=str,
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help='Write token ids this file. Must be csv or npy.')
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parser.add_argument(
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'-p',
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'--pad_id',
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type=int,
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help=
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'Token id used for padding csv input with different sequence lengths.',
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default=-1)
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parser.add_argument('-v', '--verbose', action="store_true")
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args = parser.parse_args()
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_, input_ext = os.path.splitext(args.input_file)
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_, output_ext = os.path.splitext(args.output_file)
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if (input_ext == '.csv' and output_ext == '.npy'):
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print('Converting csv to npy')
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csv_to_npy(args.input_file, args.output_file, args.pad_id, args.verbose)
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elif (input_ext == '.npy' and output_ext == '.csv'):
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print('Converting npy to csv')
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npy_to_csv(args.input_file, args.output_file, args.verbose)
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else:
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print('unknown file extensions')
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