diff --git a/python/tvm/contrib/cutlass/gen_conv2d.py b/python/tvm/contrib/cutlass/gen_conv2d.py index 4064f5c0c10a..5a616c9b6e02 100644 --- a/python/tvm/contrib/cutlass/gen_conv2d.py +++ b/python/tvm/contrib/cutlass/gen_conv2d.py @@ -128,7 +128,7 @@ def profile( If profile_all is False, return immediately after the first applicable kernel is found. If use_multiprocessing is True, compile all profiler executables in parallel. """ - B, H, W, IC = d_shape + B, _, _, IC = d_shape OC, R, S, _ = w_shape _, P, Q, _ = out_shape diff --git a/python/tvm/contrib/cutlass/gen_tensor_op.py b/python/tvm/contrib/cutlass/gen_tensor_op.py index 73f3287c8fb1..cc228737cefc 100644 --- a/python/tvm/contrib/cutlass/gen_tensor_op.py +++ b/python/tvm/contrib/cutlass/gen_tensor_op.py @@ -136,7 +136,6 @@ def get_tile_descriptions(math_inst): TileDescription([128, 256, 32], 3, [2, 4, 1], math_inst, min_cc, max_cc), TileDescription([256, 64, 32], 4, [4, 1, 1], math_inst, min_cc, max_cc), TileDescription([64, 256, 32], 4, [1, 4, 1], math_inst, min_cc, max_cc), - TileDescription([128, 128, 32], 2, [2, 2, 1], math_inst, min_cc, max_cc), TileDescription([128, 128, 32], 3, [2, 2, 1], math_inst, min_cc, max_cc), TileDescription([128, 128, 32], 4, [2, 2, 1], math_inst, min_cc, max_cc), TileDescription([128, 128, 32], 5, [2, 2, 1], math_inst, min_cc, max_cc), diff --git a/python/tvm/relay/op/contrib/cutlass.py b/python/tvm/relay/op/contrib/cutlass.py index bf17572f2500..098619cc7a82 100644 --- a/python/tvm/relay/op/contrib/cutlass.py +++ b/python/tvm/relay/op/contrib/cutlass.py @@ -87,7 +87,7 @@ def check_batch_matmul(call): rhs = batch_matmul.args[1].checked_type transpose_a = batch_matmul.attrs.transpose_a transpose_b = batch_matmul.attrs.transpose_b - return check_dtype(lhs, rhs) and transpose_a == False and transpose_b == True + return check_dtype(lhs, rhs) and not transpose_a and transpose_b def check_conv2d(call):