f9008e6366
This is an ongoing series of commits that are reformatting our Python code. Reformatting is done with `black`. If you end up having problems merging this commit because you have made changes to a python file, the best way to handle that is to run git checkout --ours <yourfile> and then reformat it with black. If you run into any problems, post to discourse about it and we will try to help. RFC Thread below: https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style Differential Revision: https://reviews.llvm.org/D150782
109 lines
3.8 KiB
Python
109 lines
3.8 KiB
Python
# RUN: %PYTHON %s | FileCheck %s
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from mlir.ir import *
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from mlir.dialects import sparse_tensor as st
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def run(f):
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print("\nTEST:", f.__name__)
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f()
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return f
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# CHECK-LABEL: TEST: testEncodingAttr1D
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@run
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def testEncodingAttr1D():
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with Context() as ctx:
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parsed = Attribute.parse(
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"#sparse_tensor.encoding<{"
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' lvlTypes = [ "compressed" ],'
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" posWidth = 16,"
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" crdWidth = 32"
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"}>"
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)
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# CHECK: #sparse_tensor.encoding<{ lvlTypes = [ "compressed" ], posWidth = 16, crdWidth = 32 }>
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print(parsed)
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casted = st.EncodingAttr(parsed)
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# CHECK: equal: True
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print(f"equal: {casted == parsed}")
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# CHECK: lvl_types: [<DimLevelType.compressed: 8>]
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print(f"lvl_types: {casted.lvl_types}")
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# CHECK: dim_ordering: None
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print(f"dim_ordering: {casted.dim_ordering}")
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# CHECK: pos_width: 16
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print(f"pos_width: {casted.pos_width}")
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# CHECK: crd_width: 32
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print(f"crd_width: {casted.crd_width}")
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created = st.EncodingAttr.get(casted.lvl_types, None, None, 0, 0)
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# CHECK: #sparse_tensor.encoding<{ lvlTypes = [ "compressed" ] }>
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print(created)
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# CHECK: created_equal: False
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print(f"created_equal: {created == casted}")
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# Verify that the factory creates an instance of the proper type.
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# CHECK: is_proper_instance: True
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print(f"is_proper_instance: {isinstance(created, st.EncodingAttr)}")
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# CHECK: created_pos_width: 0
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print(f"created_pos_width: {created.pos_width}")
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# CHECK-LABEL: TEST: testEncodingAttr2D
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@run
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def testEncodingAttr2D():
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with Context() as ctx:
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parsed = Attribute.parse(
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"#sparse_tensor.encoding<{"
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' lvlTypes = [ "dense", "compressed" ],'
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" dimOrdering = affine_map<(d0, d1) -> (d1, d0)>,"
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" posWidth = 8,"
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" crdWidth = 32"
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"}>"
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)
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# CHECK: #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], dimOrdering = affine_map<(d0, d1) -> (d1, d0)>, posWidth = 8, crdWidth = 32 }>
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print(parsed)
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casted = st.EncodingAttr(parsed)
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# CHECK: equal: True
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print(f"equal: {casted == parsed}")
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# CHECK: lvl_types: [<DimLevelType.dense: 4>, <DimLevelType.compressed: 8>]
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print(f"lvl_types: {casted.lvl_types}")
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# CHECK: dim_ordering: (d0, d1) -> (d1, d0)
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print(f"dim_ordering: {casted.dim_ordering}")
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# CHECK: pos_width: 8
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print(f"pos_width: {casted.pos_width}")
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# CHECK: crd_width: 32
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print(f"crd_width: {casted.crd_width}")
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created = st.EncodingAttr.get(
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casted.lvl_types, casted.dim_ordering, casted.higher_ordering, 8, 32
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)
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# CHECK: #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], dimOrdering = affine_map<(d0, d1) -> (d1, d0)>, posWidth = 8, crdWidth = 32 }>
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print(created)
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# CHECK: created_equal: True
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print(f"created_equal: {created == casted}")
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# CHECK-LABEL: TEST: testEncodingAttrOnTensorType
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@run
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def testEncodingAttrOnTensorType():
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with Context() as ctx, Location.unknown():
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encoding = st.EncodingAttr(
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Attribute.parse(
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"#sparse_tensor.encoding<{"
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' lvlTypes = [ "compressed" ], '
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" posWidth = 64,"
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" crdWidth = 32"
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"}>"
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)
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)
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tt = RankedTensorType.get((1024,), F32Type.get(), encoding=encoding)
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# CHECK: tensor<1024xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed" ], posWidth = 64, crdWidth = 32 }>>
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print(tt)
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# CHECK: #sparse_tensor.encoding<{ lvlTypes = [ "compressed" ], posWidth = 64, crdWidth = 32 }>
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print(tt.encoding)
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assert tt.encoding == encoding
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