[TOPI] Add valid auto tvm for Intel Graphics (apache#4078)

* add valid autotune

* fix pylint

topi/python/topi/intel_graphics/conv2d.py

@@ -23,6 +23,8 @@
 
 from tvm import autotvm
 from tvm.autotvm.task.space import SplitEntity, OtherOptionEntity
+from tvm.autotvm.task.topi_integration import deserialize_args
+from tvm.autotvm.task import get_config
 from ..nn.conv2d import conv2d, conv2d_NCHWc, conv2d_alter_layout, conv2d_infer_layout
 from ..nn.util import get_pad_tuple
 from ..nn.depthwise_conv2d import depthwise_conv2d_nchw
@@ -153,6 +155,38 @@ def tile_and_bind3d(s, tensor, z, y, x, z_factor=2, y_factor=None, x_factor=None
     s[tensor].bind(xi, thread_x)
     return xi, thread_z, thread_y, thread_x
 
+# Define template function for autotvm task
+# We define schedule template in this function instead of
+# declaration function since actual input arguments need
+# to be altered by the schedule selected.
+@autotvm.task.register("topi_intel_graphics_conv2d_NCHWc")
+def __topi_nn_conv2d_NCHWc(*args, **kwargs):
+    assert not kwargs, "Do not support kwargs in template function call"
+    data, kernel, strides, padding, dilation, layout, dtype = deserialize_args(args)
+    raw_data_shape = get_const_tuple(data.shape)
+    raw_kernel_shape = get_const_tuple(kernel.shape)
+
+    # get config here
+    cfg = get_config()
+    _create_schedule_template(cfg, data, kernel, strides, padding, dilation, layout)
+    cfg.add_flop(1)
+
+    # change shape with the value in config
+    ic_bn = cfg["tile_ic"].val if hasattr(cfg["tile_ic"], "val") else cfg["tile_ic"].size[-1]
+    oc_bn = cfg["tile_oc"].val if hasattr(cfg["tile_oc"], "val") else cfg["tile_oc"].size[-1]
+
+    new_data_shape = (raw_data_shape[0], raw_data_shape[1] // ic_bn,
+                      raw_data_shape[2], raw_data_shape[3], ic_bn)
+    new_kernel_shape = (raw_kernel_shape[0] // oc_bn, raw_kernel_shape[1] // ic_bn,
+                        raw_kernel_shape[2], raw_kernel_shape[3], ic_bn, oc_bn)
+    new_data = tvm.placeholder(new_data_shape, data.dtype)
+    new_kernel = tvm.placeholder(new_kernel_shape, kernel.dtype)
+
+    C = _decl_cl_spatialpack_NCHWc(cfg, new_data, new_kernel, strides, padding, dilation, dtype)
+    s = _schedule_conv2d_NCHWc(cfg, [C])
+
+    return s, [new_data, new_kernel, C]
+
 @conv2d_alter_layout.register(["intel_graphics"])
 def _alter_conv2d_layout(attrs, inputs, tinfo, F):
     import nnvm.symbol as sym