[TOPHUB] fix x86 backend after introducing dilation (#2129)

python/tvm/autotvm/tophub.py

@@ -21,7 +21,7 @@ AUTOTVM_TOPHUB_ROOT_PATH = os.path.join(os.path.expanduser('~'), ".tvm", "tophub
 # the version of each package
 PACKAGE_VERSION = {
     'arm_cpu': "v0.04",
-    'llvm':    "v0.02",
+    'llvm':    "v0.03",
 
     'cuda':    "v0.04",
     'rocm':    "v0.02",

topi/python/topi/x86/conv2d.py

@@ -292,6 +292,7 @@ def _alter_conv2d_layout(attrs, inputs, tinfo):
     out_channel = attrs.get_int("channels")
     padding = attrs.get_int_tuple("padding")
     strides = attrs.get_int_tuple("strides")
+    dilation = attrs.get_int_tuple("dilation")
     layout = attrs['layout']
     kh, kw = attrs.get_int_tuple("kernel_size")
 
@@ -309,10 +310,10 @@ def _alter_conv2d_layout(attrs, inputs, tinfo):
     target = tvm.target.current_target()
     # query schedule and fallback if necessary
     workload = autotvm.task.args_to_workload(
-        [data, kernel, strides, padding, out_dtype], depthwise_conv2d_nchw) \
+        [data, kernel, strides, padding, dilation, out_dtype], depthwise_conv2d_nchw) \
         if is_depthwise else \
         autotvm.task.args_to_workload(
-            [data, kernel, strides, padding, layout, out_dtype], conv2d)
+            [data, kernel, strides, padding, dilation, layout, out_dtype], conv2d)
     cfg = dispatch_ctx.query(target, workload)
     if cfg.is_fallback:
         _get_default_config(cfg, data, kernel, strides, padding, out_dtype, is_depthwise)
@@ -334,7 +335,7 @@ def _alter_conv2d_layout(attrs, inputs, tinfo):
         # Store altered operator's config
         new_kernel = tvm.placeholder((out_channel//oc_bn, kh, kw, oc_bn), dtype=kernel.dtype)
         new_workload = autotvm.task.args_to_workload(
-            [new_data, new_kernel, strides, padding, new_attrs['layout'],
+            [new_data, new_kernel, strides, padding, dilation, new_attrs['layout'],
              new_attrs['out_layout'], out_dtype], depthwise_conv2d_NCHWc)
     else:
         out_channel, _, kh, kw = get_const_tuple(kernel.shape)
@@ -345,7 +346,7 @@ def _alter_conv2d_layout(attrs, inputs, tinfo):
         new_kernel = tvm.placeholder((out_channel//oc_bn, in_channel//ic_bn, kh, kw, ic_bn, oc_bn),
                                      dtype=kernel.dtype)
         new_workload = autotvm.task.args_to_workload(
-            [new_data, new_kernel, strides, padding, new_attrs['layout'],
+            [new_data, new_kernel, strides, padding, dilation, new_attrs['layout'],
              new_attrs['out_layout'], out_dtype], conv2d_NCHWc)
 
     dispatch_ctx.update(target, new_workload, cfg)