From d1403d718431686aa4183f33978895808276c065 Mon Sep 17 00:00:00 2001
From: Ubuntu <ubuntu@ip-172-31-16-168.us-east-2.compute.internal>
Date: Wed, 29 May 2019 22:47:28 +0000
Subject: [PATCH] check unknown shape correctly.

---
 python/mxnet/gluon/parameter.py |  6 +++---
 python/mxnet/util.py            | 14 ++++++++++++++
 2 files changed, 17 insertions(+), 3 deletions(-)

diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index b6b58a24f8fe..9d6f8a3bb88b 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -30,7 +30,7 @@
 from .. import symbol, ndarray, initializer, context
 from ..context import Context, cpu
 from .. import autograd
-from .utils import _indent, _brief_print_list
+from .utils import _indent, _brief_print_list, shape_is_known
 from .. import is_np_shape
 
 # pylint: disable= invalid-name
@@ -273,7 +273,7 @@ def _finish_deferred_init(self):
             return
         init, ctx, default_init, data = self._deferred_init
         self._deferred_init = ()
-        assert self.shape is not None and np.prod(self.shape) > 0, \
+        assert shape_is_known(self.shape), \
             "Cannot initialize Parameter '%s' because it has " \
             "invalid shape: %s. Please specify in_units, " \
             "in_channels, etc for `Block`s."%(
@@ -384,7 +384,7 @@ def initialize(self, init=None, ctx=None, default_init=initializer.Uniform(),
             ctx = [ctx]
         if init is None:
             init = default_init if self.init is None else self.init
-        if not self.shape or np.prod(self.shape) <= 0:
+        if not shape_is_known(self.shape):
             if self._allow_deferred_init:
                 self._deferred_init = (init, ctx, default_init, None)
                 return
diff --git a/python/mxnet/util.py b/python/mxnet/util.py
index 29f5b78e454e..97442b126d6a 100644
--- a/python/mxnet/util.py
+++ b/python/mxnet/util.py
@@ -245,3 +245,17 @@ def _with_np_shape(*args, **kwargs):
             return func(*args, **kwargs)
 
     return _with_np_shape
+
+def shape_is_known(shape):
+    """Check whether a shape is completely known w/ or w/o np semantics."""
+    if shape is None:
+        return False
+    unknown_dim_size = -1 if is_np_shape() else 0
+    if len(shape) == 0:
+        return unknown_dim_size == -1
+    for dim_size in shape:
+        if dim_size == unknown_dim_size:
+            return False
+        assert dim_size > unknown_dim_size, "shape dimension size cannot be less than {}, while " \
+                                            "received {}".format(unknown_dim_size, dim_size)
+    return True