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Posted to issues@mxnet.apache.org by GitBox <gi...@apache.org> on 2021/02/18 13:45:16 UTC
[GitHub] [incubator-mxnet] leezu edited a comment on issue #19915: test_subgraph_exe1 fails on windows
leezu edited a comment on issue #19915:
URL: https://github.com/apache/incubator-mxnet/issues/19915#issuecomment-781353480
The first time I see a related error on master branch windows-cpu is https://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Fwindows-cpu/detail/master/2455/pipeline of https://github.com/apache/incubator-mxnet/commit/e164ceeb2c4b5fb8cacdac1f0cced683a80b70b0
```
[2021-02-16T21:06:05.273Z] _______________ test_subgraph_exe4[sym14-op_names14-default_v2] _______________
[2021-02-16T21:06:05.273Z] [gw0] win32 -- Python 3.7.0 C:\Python37\python.exe
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] sym = <Symbol convolution38>, subgraph_backend = 'default_v2'
[2021-02-16T21:06:05.273Z] op_names = ['sin', 'Convolution']
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] @pytest.mark.parametrize('subgraph_backend', ['default', 'default_v2'])
[2021-02-16T21:06:05.273Z] @pytest.mark.parametrize('sym,op_names', get_graphs())
[2021-02-16T21:06:05.273Z] def test_subgraph_exe4(sym, subgraph_backend, op_names):
[2021-02-16T21:06:05.273Z] """Use env var MXNET_SUBGRAPH_BACKEND=default to trigger graph partitioning in bind
[2021-02-16T21:06:05.273Z] and compare results of the partitioned sym and the original sym."""
[2021-02-16T21:06:05.273Z] def get_executor(sym, subgraph_backend=None, op_names=None, original_exec=None):
[2021-02-16T21:06:05.273Z] arg_shapes, _, aux_shapes = sym.infer_shape()
[2021-02-16T21:06:05.273Z] if subgraph_backend is None:
[2021-02-16T21:06:05.273Z] arg_array = [mx.nd.random.uniform(shape=shape) for shape in arg_shapes]
[2021-02-16T21:06:05.273Z] aux_array = [mx.nd.random.uniform(shape=shape) for shape in aux_shapes]
[2021-02-16T21:06:05.273Z] else:
[2021-02-16T21:06:05.273Z] arg_array = None
[2021-02-16T21:06:05.273Z] aux_array = None
[2021-02-16T21:06:05.273Z] exe = sym._bind(ctx=mx.current_context(),
[2021-02-16T21:06:05.273Z] args=arg_array if subgraph_backend is None else original_exec.arg_arrays,
[2021-02-16T21:06:05.273Z] aux_states=aux_array if subgraph_backend is None else original_exec.aux_arrays,
[2021-02-16T21:06:05.273Z] grad_req='null')
[2021-02-16T21:06:05.273Z] exe.forward()
[2021-02-16T21:06:05.273Z] return exe
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] sym, _, _ = sym
[2021-02-16T21:06:05.273Z] > original_exec = get_executor(sym)
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] tests\python\unittest\test_subgraph_op.py:237:
[2021-02-16T21:06:05.273Z] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
[2021-02-16T21:06:05.273Z] tests\python\unittest\test_subgraph_op.py:222: in get_executor
[2021-02-16T21:06:05.273Z] arg_shapes, _, aux_shapes = sym.infer_shape()
[2021-02-16T21:06:05.273Z] windows_package\python\mxnet\symbol\symbol.py:1132: in infer_shape
[2021-02-16T21:06:05.273Z] res = self._infer_shape_impl(False, *args, **kwargs)
[2021-02-16T21:06:05.273Z] windows_package\python\mxnet\symbol\symbol.py:1267: in _infer_shape_impl
[2021-02-16T21:06:05.273Z] ctypes.byref(complete)))
[2021-02-16T21:06:05.273Z] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] ret = -1
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] def check_call(ret):
[2021-02-16T21:06:05.273Z] """Check the return value of C API call.
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] This function will raise an exception when an error occurs.
[2021-02-16T21:06:05.273Z] Wrap every API call with this function.
[2021-02-16T21:06:05.273Z]
[2021-02-16T21:06:05.273Z] Parameters
[2021-02-16T21:06:05.273Z] ----------
[2021-02-16T21:06:05.273Z] ret : int
[2021-02-16T21:06:05.273Z] return value from API calls.
[2021-02-16T21:06:05.273Z] """
[2021-02-16T21:06:05.273Z] if ret != 0:
[2021-02-16T21:06:05.273Z] > raise get_last_ffi_error()
[2021-02-16T21:06:05.273Z] E mxnet.base.MXNetError: MXNetError: Error in operator convolution38: Shape inconsistent, Provided = [1,0,2,2], inferred shape=(1,3,2,2)
```
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