[Numpy] Misc fix

include/mxnet/ndarray.h

@@ -956,7 +956,7 @@ class NDArray {
     /*! \brief set the shape for ith aux data, and update storage shape if necessary */
     inline void set_aux_shape(const size_t i, const mxnet::TShape& shape) {
       aux_shapes[i] = shape;
-      if (storage_shape.ndim() > 0) {
+      if (storage_shape.ndim() >= 0) {
         if (storage_type == kRowSparseStorage && i == rowsparse::kIdx) {
           storage_shape[0] = shape[0];
         } else if (storage_type == kCSRStorage && i == csr::kIdx) {

src/c_api/c_predict_api.cc

@@ -436,6 +436,7 @@ int MXPredGetOutputShape(PredictorHandle handle,
       << "Index exceed number of outputs";
 
   const mxnet::TShape& s = p->out_shapes[out_index];
+  CHECK_GE(s.ndim(), 0);
   p->out_shapes_buffer.resize(s.ndim());
   nnvm::ShapeTypeCast(s.begin(), s.end(), p->out_shapes_buffer.data());
   *shape_data = p->out_shapes_buffer.data();

src/imperative/imperative_utils.h

@@ -31,6 +31,7 @@
 #include "../common/utils.h"
 #include "../common/exec_utils.h"
 #include "../operator/nn/mkldnn/mkldnn_base-inl.h"
+#include "../operator/operator_common.h"
 
 #ifndef MXNET_IMPERATIVE_IMPERATIVE_UTILS_H_
 #define MXNET_IMPERATIVE_IMPERATIVE_UTILS_H_
@@ -196,7 +197,7 @@ inline void SetShapeType(const Context& ctx,
 
   for (size_t i = 0; i < outputs.size(); ++i) {
     NDArrayStorageType storage_type = static_cast<NDArrayStorageType>(out_storage_types[i]);
-    if (outputs[i]->is_none() || outputs[i]->shape().ndim() == 0) {
+    if (outputs[i]->is_none() || mxnet::op::shape_is_none(outputs[i]->shape())) {
       if (is_dynamic_shape_existing) {
         // once there is dynamic shape somewhere, we could not pre-determine the shape.
         *outputs[i] = NDArray(ctx, out_types[i]);

src/kvstore/gradient_compression.cc

@@ -100,9 +100,9 @@ int64_t GradientCompression::GetCompressedSize(const int64_t original_size) {
 
 void GradientCompression::Quantize(const mxnet::NDArray &from, mxnet::NDArray *to,
                   mxnet::NDArray *residual, const int priority) {
-  CHECK(from.shape().ndim() != 0) << "source operand has zero dimension shape";
-  CHECK(to->shape().ndim() != 0) << "destination operand has zero dimension shape";
-  CHECK(residual->shape().ndim() != 0) << "residual operand has zero dimension shape";
+  CHECK(shape_is_known(from.shape())) << "source operand has undefined shape";
+  CHECK(shape_is_known(to->shape())) << "destination operand has undefined shape";
+  CHECK(shape_is_known(residual->shape())) << "residual operand has undefined shape";
   const int a = from.ctx().dev_mask();
   const int b = to->ctx().dev_mask();
   const float threshold = threshold_;
@@ -137,8 +137,8 @@ void GradientCompression::Quantize(const mxnet::NDArray &from, mxnet::NDArray *t
 
 void GradientCompression::Dequantize(const mxnet::NDArray &from, mxnet::NDArray *to,
                                      const int priority) {
-  CHECK(from.shape().ndim() != 0) << "source operands has zero dimension shape";
-  CHECK(to->shape().ndim() != 0) << "destination operand has zero dimension shape";
+  CHECK(shape_is_known(from.shape())) << "source operand has undefined shape";
+  CHECK(shape_is_known(to->shape())) << "destination operand has undefined shape";
   const int a = from.ctx().dev_mask();
   const int b = to->ctx().dev_mask();
   const float threshold = threshold_;

src/ndarray/ndarray.cc

@@ -1191,8 +1191,8 @@ void CopyFromTo(const NDArray& from, const NDArray& to, int priority, bool is_op
   CHECK(from.shape() == to.shape())
       << "operands shape mismatch"
       << "from.shape = " << from.shape() << " to.shape=" << to.shape();
-  CHECK(from.shape().ndim() != 0)
-      << "source operands have zero dimension shape";
+  CHECK(!mxnet::op::shape_is_none(from.shape()))
+      << "source operands have undefined shape";
   // important: callback must always capture by value
   const Context from_ctx = from.ctx();
   const int a = from_ctx.dev_mask();
@@ -1663,7 +1663,7 @@ bool NDArray::LegacyLoad(dmlc::Stream *strm, const uint32_t magic) {
   // load shape
   mxnet::TShape shape;
   if (!LegacyTShapeLoad(strm, &shape, magic)) return false;
-  if (shape.ndim() == 0) {
+  if (mxnet::op::shape_is_none(shape)) {
     *this = NDArray(); return true;
   }
   // load context
@@ -1711,7 +1711,10 @@ bool NDArray::Load(dmlc::Stream *strm) {
   // load shape
   mxnet::TShape shape;
   if (!shape.Load(strm)) return false;
-  if (shape.ndim() == 0) {
+  if (Imperative::Get()->is_np_comp()) {
+    common::ConvertToNumpyShape(&shape);
+  }
+  if (mxnet::op::shape_is_none(shape)) {
     *this = NDArray(); return true;
   }
 

src/ndarray/ndarray_function.h

@@ -40,7 +40,7 @@ namespace ndarray {
 struct BinaryBase {
   inline static mxnet::TShape GetShape(const mxnet::TShape &lshape, const mxnet::TShape &rshape) {
     CHECK(lshape == rshape) << "operands shape mismatch";
-    CHECK(lshape.ndim() != 0) << "source operand have zero dimension shape";
+    CHECK(!mxnet::op::shape_is_none(lshape)) << "source operand have zero dimension shape";
     return lshape;
   }
 };