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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/49980 From ``` ./python/libcst/libcst codemod remove_unused_imports.RemoveUnusedImportsWithGlean --no-format caffe2/ ``` Test Plan: Standard sandcastle tests Reviewed By: xush6528 Differential Revision: D25727359 fbshipit-source-id: c4f60005b10546423dc093d31d46deb418352286
59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
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from caffe2.python import workspace, core, lstm_benchmark, utils
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from copy import copy
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@utils.debug
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def Compare(args):
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results = []
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num_iters = 1000
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args.gpu = True
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with core.DeviceScope(core.DeviceOption(workspace.GpuDeviceType, 0)):
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for batch_size in [64, 128, 256]:
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for seq_length in [20, 100]:
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for hidden_dim in [40, 100, 400, 800]:
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args.batch_size = batch_size
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args.seq_length = seq_length
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args.hidden_dim = hidden_dim
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args.data_size = batch_size * seq_length * num_iters
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args.iters_to_report = num_iters // 3
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args.implementation = 'own'
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t_own = lstm_benchmark.Benchmark(args)
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workspace.ResetWorkspace()
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args.implementation = 'cudnn'
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t_cudnn = lstm_benchmark.Benchmark(args)
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workspace.ResetWorkspace()
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results.append((copy(args), float(t_own), float(t_cudnn)))
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print(args)
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print("t_cudnn / t_own: {}".format(t_cudnn / t_own))
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for args, t_own, t_cudnn in results:
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print("{}: cudnn time: {}, own time: {}, ratio: {}".format(
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str(args), t_cudnn, t_own, t_cudnn / t_own))
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ratio_sum = 0
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for args, t_own, t_cudnn in results:
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ratio = float(t_cudnn) / t_own
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ratio_sum += ratio
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print("hidden_dim: {}, seq_lengths: {}, batch_size: {}, num_layers: {}:"
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" cudnn time: {}, own time: {}, ratio: {}".format(
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args.hidden_dim, args.seq_length, args.batch_size,
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args.num_layers, t_cudnn, t_own, ratio))
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print("Ratio average: {}".format(ratio_sum / len(results)))
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if __name__ == '__main__':
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args = lstm_benchmark.GetArgumentParser().parse_args()
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workspace.GlobalInit([
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'caffe2',
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'--caffe2_log_level=0',
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'--caffe2_print_blob_sizes_at_exit=0',
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'--caffe2_gpu_memory_tracking=1'])
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Compare(args)
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