This is an automated email from the ASF dual-hosted git repository. taolv pushed a commit to branch v1.7.x in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.7.x by this push: new 6e956fd change error tolerance for bf16 bn (#18110) 6e956fd is described below commit 6e956fd2b78fcd20e732a1f1d915da630ea1d999 Author: rongzha1 <rong.a.zh...@intel.com> AuthorDate: Wed Apr 22 11:17:17 2020 +0800 change error tolerance for bf16 bn (#18110) --- tests/python/mkl/test_bf16_operator.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/tests/python/mkl/test_bf16_operator.py b/tests/python/mkl/test_bf16_operator.py index e4f4a93..b275c96 100644 --- a/tests/python/mkl/test_bf16_operator.py +++ b/tests/python/mkl/test_bf16_operator.py @@ -126,8 +126,8 @@ def test_bf16_bn(): bn_fp32 = mx.sym.BatchNorm(data_sym_fp32, **bn_params) bn_bf16 = mx.sym.BatchNorm(data_sym_bf16, **bn_params) - check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28), bf16_use_fp32_params=True, etol=1e-3) - check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(32, 16, 64, 64), bf16_use_fp32_params=True, etol=1e-3) + check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28), bf16_use_fp32_params=True, etol=1e-2) + check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(32, 16, 64, 64), bf16_use_fp32_params=True, etol=1e-2) @with_seed() def test_bf16_conv(): @@ -278,7 +278,7 @@ def test_bf16_fallback(): bn_params = {"eps": 2e-05, "fix_gamma": False, "use_global_stats": True, "name": "bn"} bn_fp32 = mx.sym.BatchNorm(data_sym_fp32, **bn_params) bn_bf16=mx.sym.BatchNorm(data_sym_bf16, **bn_params) - check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28, 3), bf16_use_fp32_params=True, etol=1e-3) + check_operator_accuracy(sym_fp32=bn_fp32, sym_bf16=bn_bf16, data_shape=(3, 32, 28, 28, 3), bf16_use_fp32_params=True, etol=1e-2) conv_params = {"kernel": (3, 3, 3), "num_filter": 128, "pad": (1, 1, 1), "stride": (1, 1, 1), "no_bias": True, "name": "conv"} conv_fp32 = mx.sym.Convolution(data_sym_fp32, **conv_params)