From 2789011ac6e164b002552ef29efb69d2240a133e Mon Sep 17 00:00:00 2001
From: Leyuan Wang <laurawly@gmail.com>
Date: Wed, 4 Sep 2019 14:01:33 -0700
Subject: [PATCH] fix ci

---
 topi/python/topi/intel_graphics/conv2d.py | 25 ++++++++++++-----------
 1 file changed, 13 insertions(+), 12 deletions(-)

diff --git a/topi/python/topi/intel_graphics/conv2d.py b/topi/python/topi/intel_graphics/conv2d.py
index fef95b9c6981..01ea34e2f113 100644
--- a/topi/python/topi/intel_graphics/conv2d.py
+++ b/topi/python/topi/intel_graphics/conv2d.py
@@ -171,6 +171,7 @@ def _alter_conv2d_layout(attrs, inputs, tinfo, F):
 
     layout_name = 'layout' if F == sym else 'data_layout'
     layout = attrs[layout_name]
+    kh, kw = attrs.get_int_tuple("kernel_size")
 
     dtype = data.dtype
     out_dtype = dtype if out_dtype in ("same", "") else out_dtype
@@ -191,6 +192,8 @@ def _alter_conv2d_layout(attrs, inputs, tinfo, F):
         if is_depthwise else \
         autotvm.task.args_to_workload(
             [data, kernel, strides, padding, dilation, layout, out_dtype], conv2d)
+    if is_depthwise:
+        return None
     cfg = dispatch_ctx.query(target, workload)
     if cfg.is_fallback:
         _get_default_config(cfg, data, kernel, strides, padding, out_dtype, is_depthwise)
@@ -202,19 +205,17 @@ def _alter_conv2d_layout(attrs, inputs, tinfo, F):
 
     new_data = tvm.placeholder((batch_size, in_channel//ic_bn, height, width, ic_bn),
                                dtype=data.dtype)
-    if is_depthwise:
-        raise RuntimeError("Intel graphics not supported depthwise schedule")
-    else:
-        out_channel, _, kh, kw = get_const_tuple(kernel.shape)
-        # (oc, ic, h, w) -> (OC, IC, h, w, ic, oc)
-        new_attrs['kernel_layout'] = 'OIHW%di%do' % (ic_bn, oc_bn)
 
-        # Store altered operator's config
-        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, dilation, new_attrs[layout_name],
-             new_attrs['out_layout'], out_dtype], conv2d_NCHWc)
+    out_channel, _, kh, kw = get_const_tuple(kernel.shape)
+    # (oc, ic, h, w) -> (OC, IC, h, w, ic, oc)
+    new_attrs['kernel_layout'] = 'OIHW%di%do' % (ic_bn, oc_bn)
+
+    # Store altered operator's config
+    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, dilation, new_attrs[layout_name],
+         new_attrs['out_layout'], out_dtype], conv2d_NCHWc)
 
     dispatch_ctx.update(target, new_workload, cfg)
     if F == sym: