Update fbcode symlinks for mkl-dnn ideep 2.5.2

Summary: as titled

Test Plan: buck test caffe2/test:nn

Reviewed By: VitalyFedyunin, luciang

Differential Revision: D34285331

fbshipit-source-id: 5144b3ae1dce02e995d1d633443fb660c57df101
(cherry picked from commit 61f1255)

Author: Wei Wei

caffe2/ideep/operators/order_switch_ops.cc

@@ -22,6 +22,10 @@ class IDEEPNHWC2NCHWOp final : public IDEEPOperator {
     // Thus, for iDEEP tensor, the shapes of NCHW and NHWC are identical.
     Y->init({X.get_dims(), X.get_data_type(), iformat::nchw});
     Y->feed_from(X);
+    // NOTE: This ops is only used to quantization path, setting scale
+    // to distinguish with fp32 path activation(always return NCHW format
+    // even ideep tensor has NHWC format) when convert to numpy memory.
+    Y->set_scale({1.0});
     return true;
   }
 
@@ -48,6 +52,10 @@ class IDEEPNCHW2NHWCOp final : public IDEEPOperator {
     // Thus, for iDEEP tensor, the shapes of NCHW and NHWC are identical.
     Y->init({X.get_dims(), X.get_data_type(), iformat::nhwc});
     Y->feed_from(X);
+    // NOTE: This ops is only used to quantization path, setting scale
+    // to distinguish with fp32 path activation(always return NCHW format
+    // even ideep tensor has NHWC format) when convert to numpy memory.
+    Y->set_scale({1.0});
     return true;
   }
 

caffe2/ideep/operators/utility_ops.cc

@@ -1,4 +1,4 @@
-#include "caffe2/operators/utility_ops.h"
+  #include "caffe2/operators/utility_ops.h"
 #include "caffe2/core/operator.h"
 #include "caffe2/ideep/ideep_utils.h"
 
@@ -64,7 +64,10 @@ class CopyIDEEPToCPUOp final : public IDEEPOperator {
         }
         auto* Y =
             OperatorBase::OutputTensor(0, dims, at::dtype<float>().device(CPU));
-        X.to_public(Y->template mutable_data<float>());
+        itensor temp_ten(
+            X.get_desc().to_default_format(),
+            Y->template mutable_data<float>());
+        X.reorder_to(temp_ten);
       } else {
         CAFFE_THROW("Unsupported ideep type: ",
                     static_cast<int>(X.get_data_type()));

caffe2/python/pybind_state_ideep.cc

@@ -65,10 +65,19 @@ class IDeepFetcher : public BlobFetcherBase {
         numpy_type != -1,
         "Unsupported ideep memory data type? This usually should not happen "
         "since ideep memory usually only do float and double.");
-    itensor::dims dims = atensor.get_public_format_dims();
+    itensor::dims dims;
+    bool need_reorder = atensor.need_reorder();
+    if (atensor.get_data_type() == idtype::f32 && !atensor.has_scale()) {
+      // For FP32 path, only support NCHW format input, so if atensor
+      // has NHWC format, we need reorder it to NCHW format.
+      dims = atensor.get_dims();
+      need_reorder = need_reorder || atensor.get_desc().is_nhwc();
+    } else {
+      dims = atensor.get_public_format_dims();
+    }
     std::vector<npy_intp> npy_dims(dims.begin(), dims.end());
 
-    result.copied = force_copy || atensor.need_reorder();
+    result.copied = force_copy || need_reorder;
     // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
     void* outPtr;
     if (result.copied) {
@@ -87,7 +96,12 @@ class IDeepFetcher : public BlobFetcherBase {
     }
 
     if (result.copied) {
-      atensor.to_public(outPtr);
+      if (atensor.get_data_type() == idtype::f32 && !atensor.has_scale()) {
+        itensor temp_ten(atensor.get_desc().to_default_format(), outPtr);
+        atensor.reorder_to(temp_ten);
+      } else {
+        atensor.to_public(outPtr);
+      }
     }
 
     return result;