| # RUN: %PYTHON %s | FileCheck %s |
| |
| from mlir.ir import * |
| from mlir.dialects import sparse_tensor as st |
| |
| def run(f): |
| print("\nTEST:", f.__name__) |
| f() |
| return f |
| |
| |
| # CHECK-LABEL: TEST: testEncodingAttr1D |
| @run |
| def testEncodingAttr1D(): |
| with Context() as ctx: |
| parsed = Attribute.parse( |
| '#sparse_tensor.encoding<{ dimLevelType = [ "compressed" ], ' |
| 'pointerBitWidth = 16, indexBitWidth = 32 }>') |
| print(parsed) |
| |
| casted = st.EncodingAttr(parsed) |
| # CHECK: equal: True |
| print(f"equal: {casted == parsed}") |
| |
| # CHECK: dim_level_types: [<DimLevelType.compressed: 1>] |
| print(f"dim_level_types: {casted.dim_level_types}") |
| # CHECK: dim_ordering: None |
| # Note that for 1D, the ordering is None, which exercises several special |
| # cases. |
| print(f"dim_ordering: {casted.dim_ordering}") |
| # CHECK: pointer_bit_width: 16 |
| print(f"pointer_bit_width: {casted.pointer_bit_width}") |
| # CHECK: index_bit_width: 32 |
| print(f"index_bit_width: {casted.index_bit_width}") |
| |
| created = st.EncodingAttr.get(casted.dim_level_types, None, 16, 32) |
| print(created) |
| # CHECK: created_equal: True |
| print(f"created_equal: {created == casted}") |
| |
| # Verify that the factory creates an instance of the proper type. |
| # CHECK: is_proper_instance: True |
| print(f"is_proper_instance: {isinstance(created, st.EncodingAttr)}") |
| # CHECK: created_pointer_bit_width: 16 |
| print(f"created_pointer_bit_width: {created.pointer_bit_width}") |
| |
| |
| # CHECK-LABEL: TEST: testEncodingAttr2D |
| @run |
| def testEncodingAttr2D(): |
| with Context() as ctx: |
| parsed = Attribute.parse( |
| '#sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ], ' |
| 'dimOrdering = affine_map<(d0, d1) -> (d0, d1)>, ' |
| 'pointerBitWidth = 16, indexBitWidth = 32 }>') |
| print(parsed) |
| |
| casted = st.EncodingAttr(parsed) |
| # CHECK: equal: True |
| print(f"equal: {casted == parsed}") |
| |
| # CHECK: dim_level_types: [<DimLevelType.dense: 0>, <DimLevelType.compressed: 1>] |
| print(f"dim_level_types: {casted.dim_level_types}") |
| # CHECK: dim_ordering: (d0, d1) -> (d0, d1) |
| print(f"dim_ordering: {casted.dim_ordering}") |
| # CHECK: pointer_bit_width: 16 |
| print(f"pointer_bit_width: {casted.pointer_bit_width}") |
| # CHECK: index_bit_width: 32 |
| print(f"index_bit_width: {casted.index_bit_width}") |
| |
| created = st.EncodingAttr.get(casted.dim_level_types, casted.dim_ordering, |
| 16, 32) |
| print(created) |
| # CHECK: created_equal: True |
| print(f"created_equal: {created == casted}") |
| |
| |
| # CHECK-LABEL: TEST: testEncodingAttrOnTensor |
| @run |
| def testEncodingAttrOnTensor(): |
| with Context() as ctx, Location.unknown(): |
| encoding = st.EncodingAttr(Attribute.parse( |
| '#sparse_tensor.encoding<{ dimLevelType = [ "compressed" ], ' |
| 'pointerBitWidth = 16, indexBitWidth = 32 }>')) |
| tt = RankedTensorType.get((1024,), F32Type.get(), encoding=encoding) |
| # CHECK: tensor<1024xf32, #sparse_tensor |
| print(tt) |
| # CHECK: #sparse_tensor.encoding |
| print(tt.encoding) |
| assert tt.encoding == encoding |