icemelon9 commented on a change in pull request #4644: Relay op strategy
URL: https://github.com/apache/incubator-tvm/pull/4644#discussion_r379875293
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File path: topi/python/topi/intel_graphics/conv2d.py
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@@ -159,108 +147,59 @@ def tile_and_bind3d(s, tensor, z, y, x, z_factor=2,
y_factor=None, x_factor=None
# 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):
- copy_inputs = list(inputs)
- new_attrs = {k : attrs[k] for k in attrs.keys()}
-
- if F.__name__ == 'tvm.relay.op':
- # Derive channels for frontends (e.g ONNX) that miss "channel" field.
- new_attrs["channels"] =
inputs[1].checked_type.shape[attrs['kernel_layout'].index('O')]
-
- data, kernel = tinfo[0], tinfo[1]
- batch_size, in_channel, height, width = get_const_tuple(data.shape)
+# @autotvm.task.register("topi_intel_graphics_conv2d_NCHWc")
Review comment:
removed. these are useless now
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