eric-haibin-lin closed pull request #12067: [MXNET-788] Fix for issue #11733 URL: https://github.com/apache/incubator-mxnet/pull/12067
This is a PR merged from a forked repository. As GitHub hides the original diff on merge, it is displayed below for the sake of provenance: As this is a foreign pull request (from a fork), the diff is supplied below (as it won't show otherwise due to GitHub magic): diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index b04e4a3d85c..6bc97bb71fc 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -176,3 +176,4 @@ List of Contributors * [Kou Ding](https://github.com/chinakook) * [Istvan Fehervari](https://github.com/ifeherva) * [Aaron Markham](https://github.com/aaronmarkham) +* [Sam Skalicky](https://github.com/samskalicky) diff --git a/python/mxnet/test_utils.py b/python/mxnet/test_utils.py index e963d158446..69d916ef85e 100644 --- a/python/mxnet/test_utils.py +++ b/python/mxnet/test_utils.py @@ -479,10 +479,8 @@ def assert_almost_equal(a, b, rtol=None, atol=None, names=('a', 'b'), equal_nan= """ rtol = get_rtol(rtol) atol = get_atol(atol) - if almost_equal(a, b, rtol, atol, equal_nan=equal_nan): return - index, rel = find_max_violation(a, b, rtol, atol) np.set_printoptions(threshold=4, suppress=True) msg = npt.build_err_msg([a, b], @@ -1203,10 +1201,10 @@ def check_speed(sym, location=None, ctx=None, N=20, grad_req=None, typ="whole", else: raise ValueError('typ can only be "whole" or "forward".') - def check_consistency(sym, ctx_list, scale=1.0, grad_req='write', arg_params=None, aux_params=None, tol=None, - raise_on_err=True, ground_truth=None, equal_nan=False, use_uniform=False): + raise_on_err=True, ground_truth=None, equal_nan=False, + use_uniform=False, rand_type=np.float64): """Check symbol gives the same output for different running context Parameters @@ -1223,6 +1221,11 @@ def check_consistency(sym, ctx_list, scale=1.0, grad_req='write', Optional, When flag set to true, random input data generated follows uniform distribution, not normal distribution + rand_type: np.dtype + casts the randomly generated data to this type + Optional, when input data is passed via arg_params, + defaults to np.float64 (numpy float default) + Examples -------- >>> # create the symbol @@ -1283,9 +1286,11 @@ def check_consistency(sym, ctx_list, scale=1.0, grad_req='write', for n, arr in exe_list[0].arg_dict.items(): if n not in arg_params: if use_uniform: - arg_params[n] = np.random.uniform(low=-0.92, high=0.92, size=arr.shape) + arg_params[n] = np.random.uniform(low=-0.92, high=0.92, + size=arr.shape).astype(rand_type) else: - arg_params[n] = np.random.normal(size=arr.shape, scale=scale) + arg_params[n] = np.random.normal(size=arr.shape, + scale=scale).astype(rand_type) for n, arr in exe_list[0].aux_dict.items(): if n not in aux_params: aux_params[n] = 0 diff --git a/src/operator/nn/pooling.cc b/src/operator/nn/pooling.cc index 9b6996d0feb..2380f0fc21f 100644 --- a/src/operator/nn/pooling.cc +++ b/src/operator/nn/pooling.cc @@ -377,8 +377,7 @@ We can see that Lp pooling stands between those two, in practice the most common For each window ``X``, the mathematical expression for Lp pooling is: -..math:: - f(X) = \sqrt{p}{\sum\limits_{x \in X} x^p} +:math:`f(X) = \sqrt[p]{\sum_{x}^{X} x^p}` )code" ADD_FILELINE) .set_num_inputs(1) diff --git a/tests/python/gpu/test_operator_gpu.py b/tests/python/gpu/test_operator_gpu.py index d8d34ef474d..f1cae519958 100644 --- a/tests/python/gpu/test_operator_gpu.py +++ b/tests/python/gpu/test_operator_gpu.py @@ -614,13 +614,13 @@ def test_pooling_with_type(): {'ctx': mx.cpu(0), 'pool_data': (2, 2, 10, 10), 'type_dict': {'pool_data': np.float64}}, {'ctx': mx.cpu(0), 'pool_data': (2, 2, 10, 10), 'type_dict': {'pool_data': np.float32}}] sym = mx.sym.Pooling(kernel=(3,3), pool_type='max', pooling_convention='valid', name='pool') - check_consistency(sym, ctx_list) + check_consistency(sym, ctx_list, rand_type=np.float16) sym = mx.sym.Pooling(kernel=(3,3), pool_type='max', pooling_convention='full', name='pool') - check_consistency(sym, ctx_list) + check_consistency(sym, ctx_list, rand_type=np.float16) sym = mx.sym.Pooling(kernel=(300,300), pool_type='max', global_pool=True, name='pool') - check_consistency(sym, ctx_list) + check_consistency(sym, ctx_list, rand_type=np.float16) @with_seed() @@ -765,11 +765,8 @@ def test_spatial_transformer_with_type(): check_consistency(sym, ctx_list, grad_req="add") -# Checking max pooling consistency over the data sets of different float types is problematic -# as one max value in a float32 data set may not be the max value in a float16 data set. -# This function will not be called. -@with_seed(1234) -def test_pooling_with_type(): +@with_seed() +def test_pooling_with_type2(): ctx_list = [{'ctx': mx.gpu(0), 'pool_data': (10, 2, 10, 10), 'type_dict': {'pool_data': np.float64}}, {'ctx': mx.gpu(0), 'pool_data': (10, 2, 10, 10), 'type_dict': {'pool_data': np.float32}}, {'ctx': mx.gpu(0), 'pool_data': (10, 2, 10, 10), 'type_dict': {'pool_data': np.float16}}, @@ -777,19 +774,17 @@ def test_pooling_with_type(): {'ctx': mx.cpu(0), 'pool_data': (10, 2, 10, 10), 'type_dict': {'pool_data': np.float32}}] sym = mx.sym.Pooling(name='pool', kernel=(3,3), stride=(2,2), pool_type='max') - check_consistency(sym, ctx_list) + check_consistency(sym, ctx_list, rand_type=np.float16) sym = mx.sym.Pooling(name='pool', kernel=(3,3), pad=(1,1), pool_type='avg') check_consistency(sym, ctx_list) - # this is unstable - # sym = mx.sym.Pooling(name='pool', kernel=(5,5), pad=(2,2), pool_type='max') - # check_consistency(sym, ctx_list) + sym = mx.sym.Pooling(name='pool', kernel=(5,5), pad=(2,2), pool_type='max') + check_consistency(sym, ctx_list, rand_type=np.float16) sym = mx.sym.Pooling(name='pool', kernel=(3,3), pad=(1,1), pool_type='sum') check_consistency(sym, ctx_list) - @unittest.skip("Flaky test https://github.com/apache/incubator-mxnet/issues/11517";) @with_seed() def test_pooling_versions(): ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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