From 2ecbb2776693cf45e6949e2c2b5c8bb2b0c50848 Mon Sep 17 00:00:00 2001 From: Connor Goggins Date: Thu, 27 Feb 2020 20:44:50 +0000 Subject: [PATCH] Random sampling & loss ops working --- benchmark/opperf/rules/default_params.py | 12 ++++++++++++ benchmark/opperf/utils/op_registry_utils.py | 2 +- 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/benchmark/opperf/rules/default_params.py b/benchmark/opperf/rules/default_params.py index 8ca152f46992..57d68e36cb79 100644 --- a/benchmark/opperf/rules/default_params.py +++ b/benchmark/opperf/rules/default_params.py @@ -364,6 +364,11 @@ DEFAULT_DATA_SMCE = [(1024, 1024)] DEFAULT_LABEL_SMCE = [(1024,)] +DEFAULT_LABEL_LARGE_TENSOR = [(1, 1)] +DEFAULT_DATA_CTCLOSS = [(2**32, 1, 1)] +DEFAULT_DATA_SMCE_LARGE_TENSOR = [(2**32 + 1, 1)] +DEFAULT_LABEL_SMCE_LARGE_TENSOR = [(2**32 + 1,)] + # For NN operators DEFAULT_ACT_TYPE_LR = ['leaky', 'elu', 'selu', 'gelu'] DEFAULT_ACT_TYPE_ACTIVATION = ['relu', 'sigmoid', 'softrelu', 'softsign', 'tanh'] @@ -619,6 +624,8 @@ "block_size": DEFAULT_BLOCK_SIZE_LARGE_TENSOR, "args": DEFAULT_ARGS, "index": DEFAULT_INDEX_LARGE_TENSOR, + "data_smce": DEFAULT_DATA_SMCE_LARGE_TENSOR, + "label_smce": DEFAULT_LABEL_SMCE_LARGE_TENSOR, "grid": DEFAULT_GRID_LARGE_TENSOR, "data_bilinearsampler": DEFAULT_DATA_BILINEAR_LARGE_TENSOR, "transform_type": DEFAULT_TRANSFORM_TYPE, @@ -683,6 +690,7 @@ "lhs_fill_element_0index": DEFAULT_LHS_FEI_LARGE_TENSOR, "rhs_fill_element_0index": DEFAULT_RHS_FEI_LARGE_TENSOR, "mhs": DEFAULT_MHS_LARGE_TENSOR, + "data_softmax": DEFAULT_LABEL_SOFTMAX_LARGE_TENSOR, "data_spatialtransformer": DEFAULT_DATA_ST_LARGE_TENSOR, "loc_spatialtransformer": DEFAULT_LOC_TAR_ST_LARGE_TENSOR, "target_shape": DEFAULT_LOC_TAR_ST_LARGE_TENSOR, @@ -692,6 +700,10 @@ "output_size": DEFAULT_OUTPUT_SIZE_LARGE_TENSOR, "kernel_col2im": DEFAULT_KERNEL_LARGE_TENSOR, "stride_col2im": DEFAULT_STRIDE, + "data_ctcloss": DEFAULT_DATA_CTCLOSS, + "label_ctcloss": DEFAULT_LABEL_LARGE_TENSOR, + "data_ctc_loss": DEFAULT_DATA_CTCLOSS, + "label_ctc_loss": DEFAULT_LABEL_LARGE_TENSOR, "data_rnn": DEFAULT_DATA_RNN_LARGE_TENSOR, "p_rnn": DEFAULT_P_RNN, "parameters": DEFAULT_PARAMETERS_LARGE_TENSOR, diff --git a/benchmark/opperf/utils/op_registry_utils.py b/benchmark/opperf/utils/op_registry_utils.py index 271488fcd832..9b743878172f 100644 --- a/benchmark/opperf/utils/op_registry_utils.py +++ b/benchmark/opperf/utils/op_registry_utils.py @@ -125,7 +125,7 @@ def prepare_op_inputs(op, arg_params, int64_tensor): 'MAERegressionOutput', 'SVMOutput', 'L2Normalization', 'LayerNorm', 'InstanceNorm', 'Embedding', 'Correlation', 'im2col', 'LRN', 'squeeze', 'fill_element_0index'} - custom_data_int64 = {'random_pdf_dirichlet', 'random_pdf_exponential', 'random_pdf_gamma', 'random_pdf_generalized_negative_binomial', 'random_pdf_negative_binomial', 'random_pdf_normal', 'random_pdf_poisson', 'random_pdf_uniform', 'sample_exponential', 'sample_normal', 'sample_poisson', 'sample_uniform', 'sample_gamma', 'sample_generalized_negative_binomial', 'sample_negative_binomial'} + custom_data_int64 = {'random_pdf_dirichlet', 'random_pdf_exponential', 'random_pdf_gamma', 'random_pdf_generalized_negative_binomial', 'random_pdf_negative_binomial', 'random_pdf_normal', 'random_pdf_poisson', 'random_pdf_uniform', 'sample_exponential', 'sample_normal', 'sample_poisson', 'sample_uniform', 'sample_gamma', 'sample_generalized_negative_binomial', 'sample_negative_binomial', 'CTCLoss', 'ctc_loss'} int_only = {'random_randint'} float_only = {'log_softmax', 'softmax', 'softmin'}