global numpy shape flag

include/mxnet/c_api.h

@@ -1173,7 +1173,8 @@ MXNET_DLL int MXAutogradIsTraining(bool* curr);
 MXNET_DLL int MXIsNumpyShape(bool* curr);
 /*!
  * \brief set numpy compatibility switch
- * \param is_np_shape 1 when numpy shape semantics is on, 0 when off
+ * \param is_np_shape 1 when numpy shape semantics is thread local on,
+ *        2 when numpy shape semantics is global on and 0 when off
  * \param prev returns the previous status before this set
  * \return 0 when success, -1 when failure happens
  */

include/mxnet/imperative.h

@@ -35,6 +35,17 @@
 #include "./ndarray.h"
 
 namespace mxnet {
+  /*! \brief there are three numpy shape flags based on priority.
+   * GlobalOn
+   *   turn on numpy shape flag globally, it includes thread local.
+   *   The flag can be seen in any thread.
+   * ThreadLocalOn
+   *   only turn on thread local numpy shape flag, it cannot be seen
+   *   in other threads.
+   * Off
+   *   turn off numpy shape flag globally.
+   * */
+  enum NumpyShape{Off, ThreadLocalOn, GlobalOn};
 /*! \brief runtime functions for NDArray */
 class Imperative {
  public:
@@ -97,14 +108,30 @@ class Imperative {
       is_recording_ = is_recording;
       return old;
   }
-  /*! brief whether numpy compatibility is on. */
+  /*! \brief whether numpy compatibility is on. */
   bool is_np_shape() const {
-    return is_np_shape_;
+    if (is_np_shape_global_) {
+      return true;
+    }
+    return is_np_shape_thread_local_;
   }
-  /*! brief turn on or turn off numpy compatibility switch. */
-  bool set_is_np_shape(bool is_np_shape) {
-    bool old = is_np_shape_;
-    is_np_shape_ = is_np_shape;
+  /*! \brief specify numpy compatibility off, thread local on or global on. */
+  bool set_is_np_shape(int is_np_shape) {
+    NumpyShape flag = static_cast<NumpyShape>(is_np_shape);
+    bool old = this->is_np_shape();
+    switch (flag) {
+      case GlobalOn:
+        is_np_shape_global_ = true;
+        is_np_shape_thread_local_ = true;
+        break;
+      case ThreadLocalOn:
+        is_np_shape_thread_local_ = true;
+        break;
+      case Off:
+        is_np_shape_global_ = false;
+        is_np_shape_thread_local_ = false;
+        break;
+    }
     return old;
   }
   /*! \brief to record operator, return corresponding node. */
@@ -177,14 +204,15 @@ class Imperative {
   static thread_local bool is_recording_;
   // TOOD(junwu): Added numpy compatibility switch for backward compatibility.
   // Delete it in the next major release.
-  static thread_local bool is_np_shape_;
+  static thread_local bool is_np_shape_thread_local_;
 #else
   static MX_THREAD_LOCAL bool is_train_;
   static MX_THREAD_LOCAL bool is_recording_;
   // TOOD(junwu): Added numpy compatibility switch for backward compatibility.
   // Delete it in the next major release.
-  static MX_THREAD_LOCAL bool is_np_shape_;
+  static MX_THREAD_LOCAL bool is_np_shape_thread_local_;
 #endif
+  bool is_np_shape_global_{false};
   /*! \brief node count used for naming */
   std::atomic<uint64_t> node_count_{0};
   /*! \brief variable count used for naming */

src/c_api/c_api_ndarray.cc

@@ -284,7 +284,7 @@ int MXIsNumpyShape(bool* curr) {
 
 int MXSetIsNumpyShape(int is_np_shape, int* prev) {
   API_BEGIN();
-  *prev = Imperative::Get()->set_is_np_shape(static_cast<bool>(is_np_shape));
+  *prev = Imperative::Get()->set_is_np_shape(is_np_shape);
   API_END();
 }
 

src/imperative/imperative.cc

@@ -25,11 +25,11 @@ namespace mxnet {
 #if DMLC_CXX11_THREAD_LOCAL
 thread_local bool Imperative::is_train_ = false;
 thread_local bool Imperative::is_recording_ = false;
-thread_local bool Imperative::is_np_shape_ = false;
+thread_local bool Imperative::is_np_shape_thread_local_ = false;
 #else
 MX_THREAD_LOCAL bool Imperative::is_train_ = false;
 MX_THREAD_LOCAL bool Imperative::is_recording_ = false;
-MX_THREAD_LOCAL bool Imperative::is_np_shape_ = false;
+MX_THREAD_LOCAL bool Imperative::is_np_shape_thread_local_ = false;
 #endif
 
 Imperative* Imperative::Get() {

tests/python/unittest/test_thread_local.py

@@ -16,14 +16,16 @@
 # under the License.
 
 import threading
+import numpy as np
 import mxnet as mx
 from mxnet import context, attribute, name
 from mxnet.gluon import block
 from mxnet.context import Context
 from mxnet.attribute import AttrScope
 from mxnet.name import NameManager
-from mxnet.test_utils import set_default_context
-from mxnet.util import _NumpyArrayScope
+from mxnet.test_utils import assert_almost_equal, set_default_context
+from mxnet.util import _NumpyArrayScope, set_np_shape
+
 
 def test_context():
     ctx_list = []
@@ -199,6 +201,26 @@ def g():
     assert status[0], "Spawned thread didn't set status correctly"
 
 
+def test_np_global_shape():
+    set_np_shape(2)
+    data = []
+
+    def f():
+        # scalar
+        data.append(mx.np.ones(shape=()))
+        # zero-dim
+        data.append(mx.np.ones(shape=(0, 1, 2)))
+
+    thread = threading.Thread(target=f)
+    thread.start()
+    thread.join()
+
+    assert_almost_equal(data[0].asnumpy(), np.ones(shape=()))
+    assert_almost_equal(data[1].asnumpy(), np.ones(shape=(0, 1, 2)))
+    # turn off the numpy shape flag
+    set_np_shape(0)
+
+
 if __name__ == '__main__':
     import nose
     nose.runmodule()