# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # The set of ops that support fp16 calculation and are considered numerically- # safe and performance-critical. These ops are always converted to fp16. FP16_WHITE_LIST = { 'conv2d', 'matmul', 'matmul_v2', 'max_pool2d_with_index', 'mul', 'fake_quantize_dequantize_abs_max', 'fake_quantize_dequantize_moving_average_abs_max', } # The set of ops that support fp16 calculation and are considered numerically- # dangerous and whose effects may also be observed in downstream ops. FP16_BLACK_LIST = { 'tan', 'acos', 'asin', 'sinh', 'cosh', 'atanh', 'tanh_shrink', 'cos_sim', 'erfinv', 'exp', 'expm1', 'log', 'log10', 'log2', 'reciprocal', 'rsqrt', 'pow', 'square', 'reduce_sum', 'mean', 'reduce_mean', 'reduce_prod', 'cumprod', 'cumsum', 'dist', 'pnorm', 'frobenius_norm', 'renorm', 'group_norm', 'layer_norm', 'softmax', 'softmin', 'softplus', 'log_softmax', 'softmax_with_cross_entropy', 'sigmoid_cross_entropy_with_logits', 'c_softmax_with_cross_entropy', 'cross_entropy', 'cross_entropy2', 'nll_loss', 'huber_loss', 'triplet_margin_loss', 'log_loss', 'hsigmoid_loss', 'margin_cross_entropy', } # FP16 performance of grad op is worse than that of FP32. Use FP32 by default. FP16_EXTRA_BLACK_LIST = { 'linear_interp_v2', 'nearest_interp_v2', 'bilinear_interp_v2', 'bicubic_interp_v2', 'trilinear_interp_v2', 'lookup_table', 'lookup_table_v2', 'scatter', 'depthwise_conv2d', } BF16_WHITE_LIST = {'conv2d', 'matmul_v2'} BF16_BLACK_LIST = set() # At OD level, ops in WHITE_LIST will use FP16/BF16 and the others will use FP32. def white_list(): white_list = { "float16": { "OD": FP16_WHITE_LIST, "O1": FP16_WHITE_LIST, "O2": FP16_WHITE_LIST, }, "bfloat16": { "OD": BF16_WHITE_LIST, "O1": BF16_WHITE_LIST, "O2": BF16_WHITE_LIST, }, } return white_list def black_list(): black_list = { "float16": { "OD": set(), "O1": FP16_BLACK_LIST | FP16_EXTRA_BLACK_LIST, "O2": FP16_EXTRA_BLACK_LIST, }, "bfloat16": {"OD": set(), "O1": BF16_BLACK_LIST, "O2": set()}, } return black_list