Ensure that correct transformed matrices are used in CpuFullyConnected

Execution pack of CpuFullyConnected was altered explicitly with local
objects that were getting out of scope. Leading to incorrect results or
memory related issues.

Track transformed weights and register the weights matrix explicitly
during execution honoring the object lifetime scope.

Resolves: COMPMID-4762, COMPMID-4764

Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I53449c377fb1cfccdf5e6f9505d963518748c318
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/c/VisualCompute/ComputeLibrary/+/349345
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Comments-Addressed: bsgcomp <bsgcomp@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6092
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 34 insertions, 22 deletions

diff --git a/src/runtime/cpu/operators/CpuFullyConnected.cpp b/src/runtime/cpu/operators/CpuFullyConnected.cpp
index e7808fbc82..eeabce0753 100644
--- a/src/runtime/cpu/operators/CpuFullyConnected.cpp
+++ b/src/runtime/cpu/operators/CpuFullyConnected.cpp
@@ -150,9 +150,11 @@ CpuFullyConnected::CpuFullyConnected()
       _flattened_src(),
       _converted_weights(),
       _reshaped_weights(),
+      _trans_weights(),
+      _trans_weights_idx(AuxTensorIdx::Count),
       _aux_mem(Count),
-      _are_weights_converted(false),
-      _are_weights_reshaped(false),
+      _needs_weights_conversion(false),
+      _needs_weights_reshape(false),
       _is_fc_after_conv(false),
       _is_quantized_asymmetric(false),
       _is_prepared(false)
@@ -230,11 +232,13 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei
                                                            dst,
                                                            fc_info));
 
-    _are_weights_converted   = true;
-    _are_weights_reshaped    = fc_info.transpose_weights ? fc_info.are_weights_reshaped : true;
-    _is_fc_after_conv        = true;
-    _is_quantized_asymmetric = is_data_type_quantized_asymmetric(src->data_type());
-    _is_prepared             = false;
+    _needs_weights_conversion = false;
+    _needs_weights_reshape    = fc_info.transpose_weights ? !fc_info.are_weights_reshaped : false;
+    _needs_weights_reshape    = _needs_weights_reshape && !fc_info.retain_internal_weights;
+    _is_fc_after_conv         = true;
+    _is_quantized_asymmetric  = is_data_type_quantized_asymmetric(src->data_type());
+    _is_prepared              = false;
+    _trans_weights_idx        = AuxTensorIdx::Count;
 
     // With the Fully Connected layer we can have 4 different cases:
     //  1) Convolution layer -> Fully Connected layer without batches
@@ -258,12 +262,13 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei
     }
 
     // Reshape weights if needed
-    if(!_are_weights_reshaped)
+    if(_needs_weights_reshape)
     {
         // Reshape the weights
         _transpose_weights = std::make_unique<kernels::CpuTransposeKernel>();
         _transpose_weights->configure(weights, &_reshaped_weights);
-        weights_to_use = &_reshaped_weights;
+        weights_to_use     = &_reshaped_weights;
+        _trans_weights_idx = AuxTensorIdx::TransposedWeights;
     }
 
     // Convert weights if needed
@@ -276,8 +281,9 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei
                                     src->tensor_shape(),
                                     fc_info.weights_trained_layout);
 
-        weights_to_use         = &_converted_weights;
-        _are_weights_converted = false;
+        weights_to_use            = &_converted_weights;
+        _needs_weights_conversion = true;
+        _trans_weights_idx        = AuxTensorIdx::ConvertedWeights;
     }
 
     if(_is_fc_after_conv)
@@ -291,7 +297,11 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei
         configure_fc_fc(src, weights_to_use, biases, dst, fc_info.activation_info);
     }
 
-    _are_weights_reshaped = _are_weights_reshaped || fc_info.retain_internal_weights;
+    // Retain the tensorinfo with the weights to use
+    if(_needs_weights_reshape || _needs_weights_conversion)
+    {
+        _trans_weights = *weights_to_use;
+    }
 
     // Set auxiliary memory requirements
     auto gemm_mem_req = (_is_quantized_asymmetric) ? _mm_gemmlowp->workspace() : _mm_gemm->workspace();
@@ -308,7 +318,7 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei
     }
     else
     {
-        _aux_mem[TransposedWeights] = MemoryInfo(offset_int_vec(TransposedWeights), MemoryLifetime::Persistent, _reshaped_weights.total_size());
+        _aux_mem[TransposedWeights] = MemoryInfo(offset_int_vec(TransposedWeights), _needs_weights_conversion ? MemoryLifetime::Prepare : MemoryLifetime::Persistent, _reshaped_weights.total_size());
         _aux_mem[ConvertedWeights]  = MemoryInfo(offset_int_vec(ConvertedWeights), MemoryLifetime::Persistent, _converted_weights.total_size());
     }
     _aux_mem[FlattenedSrc] = MemoryInfo(offset_int_vec(FlattenedSrc), MemoryLifetime::Temporary, _flattened_src.total_size());
@@ -401,6 +411,7 @@ void CpuFullyConnected::run(ITensorPack &tensors)
     auto src = tensors.get_const_tensor(ACL_SRC_0);
 
     CpuAuxTensorHandler flattened_src(offset_int_vec(FlattenedSrc), _flattened_src, tensors, false);
+    CpuAuxTensorHandler transformed_wei(offset_int_vec(_trans_weights_idx), _trans_weights, tensors, false);
 
     // Linearize src if it comes from a convolutional layer
     if(_is_fc_after_conv)
@@ -411,6 +422,10 @@ void CpuFullyConnected::run(ITensorPack &tensors)
 
     ITensorPack gemm_pack = tensors;
     gemm_pack.add_const_tensor(ACL_SRC_0, (_is_fc_after_conv) ? flattened_src.get() : src);
+    if(_needs_weights_reshape || _needs_weights_conversion)
+    {
+        gemm_pack.add_const_tensor(ACL_SRC_1, transformed_wei.get());
+    }
 
     // Run matrix multiply
     if(_is_quantized_asymmetric)
@@ -436,7 +451,7 @@ void CpuFullyConnected::prepare(ITensorPack &tensors)
         const ITensor *cur_weights = weights;
 
         // Reshape of the weights (happens only once)
-        if(!_are_weights_reshaped)
+        if(_needs_weights_reshape)
         {
             // Run reshape weights kernel and mark weights as unused
             ITensorPack transpose_pack{ { ACL_SRC, weights }, { ACL_DST, reshaped_weights.get() } };
@@ -444,32 +459,29 @@ void CpuFullyConnected::prepare(ITensorPack &tensors)
 
             cur_weights->mark_as_unused();
             cur_weights = reshaped_weights.get();
-
-            _are_weights_reshaped = true;
         }
 
         // Convert weights if needed (happens only once)
-        if(!_are_weights_converted)
+        if(_needs_weights_conversion)
         {
             ITensorPack convert_pack{ { ACL_SRC, cur_weights }, { ACL_DST, converted_weights.get() } };
             _convert_weights->run(convert_pack);
 
             cur_weights->mark_as_unused();
             cur_weights = converted_weights.get();
-
-            _are_weights_converted = true;
         }
 
-        tensors.add_const_tensor(ACL_SRC_1, cur_weights);
+        ITensorPack gemm_pack = tensors;
+        gemm_pack.add_const_tensor(ACL_SRC_1, cur_weights);
 
         // Prepare GEMM prepare and release unused weights
         if(!_is_quantized_asymmetric)
         {
-            _mm_gemm->prepare(tensors);
+            _mm_gemm->prepare(gemm_pack);
         }
         else
         {
-            _mm_gemmlowp->prepare(tensors);
+            _mm_gemmlowp->prepare(gemm_pack);
         }
 
         _is_prepared = true;