[GitHub] [incubator-tvm] icemelon9 commented on a change in pull request #6373: Register shape functions for some image related ops

[GitBox <gi...@apache.org>]

icemelon9 commented on a change in pull request #6373:
URL: https://github.com/apache/incubator-tvm/pull/6373#discussion_r495102806



##########
File path: python/tvm/relay/op/image/_image.py
##########
@@ -40,6 +40,33 @@ def compute_resize(attrs, inputs, out_type):
 
 reg.register_injective_schedule("image.resize")
 
+@script
+def _resize_func(image_shape, size, height_axis, width_axis, channel_axis):

Review comment:
       change the name to `_resize_shape_func`.

##########
File path: python/tvm/relay/op/image/_image.py
##########
@@ -118,3 +162,19 @@ def compute_grid_sample(attrs, inputs, out_dtype):
     return [topi.image.grid_sample(inputs[0], inputs[1], method, layout)]
 
 reg.register_injective_schedule("image.grid_sample")
+
+@script
+def _grid_sample_func(data, grid):
+    out = output_tensor((4,), "int64")
+    out[0] = int64(data[0])
+    out[1] = int64(data[1])
+    out[2] = int64(grid[2])
+    out[3] = int64(grid[3])

Review comment:
       same question here. different layout?

##########
File path: python/tvm/relay/op/image/_image.py
##########
@@ -40,6 +40,33 @@ def compute_resize(attrs, inputs, out_type):
 
 reg.register_injective_schedule("image.resize")
 
+@script
+def _resize_func(image_shape, size, height_axis, width_axis, channel_axis):
+    out = output_tensor((4,), "int64")
+    out[0] = int64(image_shape[0])
+    out[height_axis] = int64(size[0])
+    out[width_axis] = int64(size[1])
+    out[channel_axis] = image_shape[channel_axis]
+    return out
+
+@reg.register_shape_func("image.resize", False)
+def resize_func(attrs, inputs, _):

Review comment:
       change the name to `resize_shape_func`

##########
File path: python/tvm/relay/op/image/_image.py
##########
@@ -40,6 +40,33 @@ def compute_resize(attrs, inputs, out_type):
 
 reg.register_injective_schedule("image.resize")
 
+@script
+def _resize_func(image_shape, size, height_axis, width_axis, channel_axis):
+    out = output_tensor((4,), "int64")
+    out[0] = int64(image_shape[0])
+    out[height_axis] = int64(size[0])
+    out[width_axis] = int64(size[1])
+    out[channel_axis] = image_shape[channel_axis]
+    return out
+
+@reg.register_shape_func("image.resize", False)
+def resize_func(attrs, inputs, _):
+    """
+    Shape function for resize op.
+    """
+    layout = attrs.layout
+    height_axis = width_axis = channel_axis = 1
+    for i, letter in enumerate(layout):
+        if letter == "H":
+            height_axis = i
+        if letter == "W":
+            width_axis = i
+        if letter == "C":
+            channel_axis = i
+    size = get_const_tuple(attrs.size)
+    return [_resize_func(inputs[0], convert(size), convert(height_axis),

Review comment:
       Could you also provide batch axis to the shape func as well?

##########
File path: python/tvm/relay/op/image/_image.py
##########
@@ -109,6 +136,23 @@ def compute_affine_grid(attrs, inputs, out_dtype):
 
 reg.register_injective_schedule("image.affine_grid")
 
+@script
+def _affine_grid_func(data, target_shape):
+    out = output_tensor((4,), "int64")
+    out[0] = int64(data[0])
+    out[1] = int64(2)
+    out[2] = int64(target_shape[0])

Review comment:
       do we support different layout for `affine_grid`?




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