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python/tvm/tir/schedule/schedule.py

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@@ -2137,7 +2137,9 @@ def transform_layout(
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Examples
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--------
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Before transform_layout, in TensorIR, the IR is:
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.. code-block:: python
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@T.prim_func
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def before_transform_layout(a: T.handle, c: T.handle) -> None:
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A = T.match_buffer(a, (128, 128), "float32")
@@ -2151,14 +2153,20 @@ def before_transform_layout(a: T.handle, c: T.handle) -> None:
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with T.block("C"):
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vi, vj = T.axis.remap("SS", [i, j])
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C[vi, vj] = B[vi, vj] + 1.0
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Create the schedule and do transform_layout:
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.. code-block:: python
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sch = tir.Schedule(before_storage_align)
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sch.transform_layout(sch.get_block("B"), buffer_index=0, is_write_index=True,
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index_map=lambda m, n: (m // 16, n // 16, m % 16, n % 16))
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print(sch.mod["main"].script())
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After applying transform_layout, the IR becomes:
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.. code-block:: python
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@T.prim_func
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def two_elementwise_transformed_intermediate_buffer(a: T.handle, c: T.handle) -> None:
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A = T.match_buffer(a, (128, 128), "float32")
@@ -2172,6 +2180,7 @@ def two_elementwise_transformed_intermediate_buffer(a: T.handle, c: T.handle) ->
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with T.block("C"):
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vi, vj = T.axis.remap("SS", [i, j])
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C[vi, vj] = B[vi // 16, vj // 16, vi % 16, vj % 16] + 1.0
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"""
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if callable(index_map):
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index_map = IndexMap.from_func(index_map)

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