jcf94 commented on a change in pull request #7161:
URL: https://github.com/apache/tvm/pull/7161#discussion_r548502307
##########
File path: python/tvm/relay/op/strategy/x86.py
##########
@@ -364,9 +373,9 @@ def dense_strategy_cpu(attrs, inputs, out_type, target):
def batch_matmul_strategy_cpu(attrs, inputs, out_type, target):
"""batch_matmul x86 strategy"""
strategy = _op.OpStrategy()
- if is_dynamic(out_type):
+ if is_dynamic(out_type) or is_auto_scheduler_enabled():
Review comment:
I feel confused about the condition here. Does `is_dynamic(out_type)`
just means the output shape has not been computed rather than this is a dynamic
shape op?
##########
File path: python/tvm/topi/nn/batch_matmul.py
##########
@@ -36,14 +36,25 @@ def batch_matmul(x, y, oshape=None):
Explicit intended output shape of the computation. Can be useful in
cases
with dynamic input shapes.
+ auto_scheduler_rewritten_layout: str = ""
+ The layout after auto-scheduler's layout rewrite pass.
+
Returns
-------
output : tvm.te.Tensor
3-D with shape [batch, M, N]
"""
assert len(x.shape) == 3 and len(y.shape) == 3, "only support 3-dim
batch_matmul"
x_shape = get_const_tuple(x.shape)
- y_shape = get_const_tuple(y.shape)
+ if auto_scheduler_rewritten_layout:
+ # Infer shape for the rewritten layout
+ y_shape = auto_scheduler.get_shape_from_rewritten_layout(
+ auto_scheduler_rewritten_layout, ["b", "j", "k"]
+ )
+ auto_scheduler.remove_index_check(y)
+ else:
+ y_shape = get_const_tuple(y.shape)
+
Review comment:
Forget to add the `auto_scheduler.rewrite_compute_body` in the end of
this function?
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