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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18886 Expose tensor filler util to Python and add a unit test (both C++/Python) Reviewed By: salexspb Differential Revision: D14784470 fbshipit-source-id: bb8e013d1755c27c166e87d5a8491a97c65d3d8d
21 lines
854 B
Python
21 lines
854 B
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from caffe2.python import core, test_util, workspace
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class TestFiller(test_util.TestCase):
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def test_filler(self):
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net = core.Net("test_filler")
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net.Concat(["X0", "X1", "X2"], ["concat_out", "split_info"])
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self.assertFalse(workspace.HasBlob("X0"))
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input_dim = (30, 20)
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workspace.FillRandomNetworkInputs(net, [[input_dim, input_dim, input_dim]], [["float", "float", "float"]])
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self.assertTrue(workspace.HasBlob("X0"))
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self.assertEqual(workspace.FetchBlob("X0").shape, input_dim)
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with self.assertRaises(RuntimeError):
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# Filler should throw if number of input dims/types is mismatched.
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workspace.FillRandomNetworkInputs(net, [[input_dim]], [["float"]])
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