[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #17014: [NumPy] Add NumPy support for norm

[GitBox <gi...@apache.org>]

haojin2 commented on a change in pull request #17014: [NumPy] Add NumPy support for norm
URL: https://github.com/apache/incubator-mxnet/pull/17014#discussion_r364482831
 
 

 ##########
 File path: src/operator/numpy/linalg/np_norm.cc
 ##########
 @@ -0,0 +1,182 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file np_norm-.cc
+ * \brief CPU registration of np.linalg.norm
+ */
+
+#include "./np_norm-inl.h"
+
+namespace mxnet {
+namespace op {
+
+DMLC_REGISTER_PARAMETER(NumpyNormParam);
+
+inline bool NumpyLpNormShape(const nnvm::NodeAttrs& attrs,
+                             mxnet::ShapeVector *in_attrs,
+                             mxnet::ShapeVector *out_attrs) {
+  if (!shape_is_known((*in_attrs)[0])) return false;
+  const NumpyNormParam& param = nnvm::get<NumpyNormParam>(attrs.parsed);
+  const int ndim = (*in_attrs)[0].ndim();
+  if ((!param.axis.has_value() && param.flag != 0 && ndim > 2) ||
+      (param.axis.has_value() && param.axis.value().ndim() > 2))
+    LOG(FATAL) << "Improper number of dimensions to norm.";
+  if (!param.axis.has_value()) {
+    if ((ndim == 0 && param.flag != 0) ||  // for scalar
+        (ndim == 1 && (param.flag == 2)) ||
+        (ndim >= 2 && (param.ord == 0 || param.ord > 2 || param.ord < -2))) {
+      LOG(FATAL) << "Invalid norm order for inputs.";
+    }
+  } else {
+    if ((param.axis.value().ndim() == 0 && param.flag != 0) ||  // for scalar
+        (param.axis.value().ndim() == 1 && (param.flag == 2)) ||
+        (param.axis.value().ndim() == 2 && (param.ord == 0 || param.ord > 2 || param.ord < -2))) {
+      LOG(FATAL) << "Invalid norm order for inputs.";
+    }
+  }
+  if (!param.keepdims && (*in_attrs)[0].ndim() == 1) {
+    SHAPE_ASSIGN_CHECK(*out_attrs, 0, TShape(0, -1));
+  } else {
+    SHAPE_ASSIGN_CHECK(*out_attrs, 0,
+                       ReduceAxesShapeImpl((*in_attrs)[0], param.axis, param.keepdims, false));
+  }
+  return true;
+}
+
+inline bool NumpyMatrixNormShape(const nnvm::NodeAttrs& attrs,
+                                   mxnet::ShapeVector *in_attrs,
 
 Review comment:
   alignment.

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