[TOPI] Fix x86 conv2d template when tuning with unpacked layout (apac…

…he#5938) * fix x86 conv2d and conv2d_transpose template * address comments
neo-ai · Jul 14, 2020 · d8a4166 · d8a4166
1 parent 652d511
commit d8a4166
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Showing 3 changed files with 10 additions and 8 deletions.
diff --git a/topi/python/topi/x86/conv2d_avx_1x1.py b/topi/python/topi/x86/conv2d_avx_1x1.py
@@ -73,6 +73,7 @@ def _schedule_conv_NCHWc(s, cfg, data_vec, kernel_vec, conv_out, last):
         s[data_vec].parallel(parallel_axis)
         data_vec = data_vec.op.input_tensors[0]
 
+    oc_bn = cfg["tile_oc"].size[-1]
     if isinstance(kernel_vec.op, tvm.te.ComputeOp) and \
             kernel_vec.name == 'kernel_vec':
         # data and kernel are not pre-computed, schedule layout transform here.
@@ -84,7 +85,6 @@ def _schedule_conv_NCHWc(s, cfg, data_vec, kernel_vec, conv_out, last):
 
         oc_chunk, ic_chunk, oh, ow, ic_block, oc_block = s[kernel_vec].op.axis
         s[kernel_vec].reorder(oc_chunk, oh, ic_chunk, ow, ic_block, oc_block)
-        oc_bn = cfg["tile_oc"].size[-1]
         if oc_bn > 1:
             s[kernel_vec].vectorize(oc_block)
         parallel_axis = s[kernel_vec].fuse(oc_chunk, oh)

diff --git a/topi/python/topi/x86/conv2d_avx_common.py b/topi/python/topi/x86/conv2d_avx_common.py
@@ -95,6 +95,7 @@ def _schedule_conv_NCHWc(s, cfg, data_vec, kernel_vec, conv_out, last):
         s[data_vec].parallel(parallel_axis)
         data_vec = data_vec.op.input_tensors[0]
 
+    oc_bn = cfg["tile_oc"].size[-1]
     if isinstance(kernel_vec.op, tvm.te.ComputeOp) and \
             kernel_vec.name == 'kernel_vec':
         # data and kernel are not pre-computed, schedule layout transform here.
@@ -106,7 +107,6 @@ def _schedule_conv_NCHWc(s, cfg, data_vec, kernel_vec, conv_out, last):
 
         oc_chunk, ic_chunk, oh, ow, ic_block, oc_block = s[kernel_vec].op.axis
         s[kernel_vec].reorder(oc_chunk, oh, ic_chunk, ow, ic_block, oc_block)
-        oc_bn = cfg["tile_oc"].size[-1]
         if oc_bn > 1:
             s[kernel_vec].vectorize(oc_block)
         parallel_axis = s[kernel_vec].fuse(oc_chunk, oh)

diff --git a/topi/python/topi/x86/conv2d_transpose.py b/topi/python/topi/x86/conv2d_transpose.py
@@ -40,14 +40,16 @@ def _callback(op):
             conv_out = op.input_tensors[0]
             # retrieve data
             data_vec = conv_out.op.input_tensors[0]
-            data_pad = data_vec.op.input_tensors[0]
-            data_dilate = data_pad.op.input_tensors[0]
-            s[data_dilate].compute_inline()
-            s[data_pad].compute_inline()
+            if isinstance(data_vec, te.ComputeOp):
+                data_pad = data_vec.op.input_tensors[0]
+                data_dilate = data_pad.op.input_tensors[0]
+                s[data_dilate].compute_inline()
+                s[data_pad].compute_inline()
             # retrieve kernel
             kernel_vec = conv_out.op.input_tensors[1]
-            kernel_transform = kernel_vec.op.input_tensors[0]
-            s[kernel_transform].compute_inline()
+            if isinstance(kernel_vec, te.ComputeOp):
+                kernel_transform = kernel_vec.op.input_tensors[0]
+                s[kernel_transform].compute_inline()
 
     traverse_inline(s, outs[0].op, _callback)
     return s