wehub-resource-sync
904 lines
29 KiB
Python
904 lines
29 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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import pytest
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import tvm
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import tvm.testing
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from tvm import relax, tirx
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from tvm.ir import Op, VDevice
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from tvm.script import relax as R
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def test_op_correctness():
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x = relax.Var("x", R.Tensor((2, 3, 4, 5), "float32"))
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assert relax.op.unique(x).op == Op.get("relax.unique")
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def _check_inference(bb: relax.BlockBuilder, call: relax.Call, expected_ty: relax.Type):
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ret = bb.normalize(call)
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tvm.ir.assert_structural_equal(ret.ty, expected_ty)
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def test_unique_infer_ty():
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bb = relax.BlockBuilder()
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vdev0 = VDevice("llvm")
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x0 = relax.Var("x", R.Tensor((2, 3, 4), "float32"))
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x1 = relax.Var("x", R.Tensor("float32", ndim=3))
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x2 = relax.Var("x", R.Tensor("float32"))
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x3 = relax.Var("x", R.Tensor((2, 3, 4)))
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x4 = relax.Var("x", R.Tensor((2, 3, 4), "float32", vdev0))
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_check_inference(
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bb,
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relax.op.unique(
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x0, return_index=False, return_inverse=False, return_counts=False, axis=None
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),
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relax.TensorType(dtype="float32", ndim=1),
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)
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_check_inference(
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bb,
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relax.op.unique(
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x4, return_index=False, return_inverse=False, return_counts=False, axis=None
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),
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relax.TensorType(dtype="float32", ndim=1, vdevice=vdev0),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=False, return_inverse=False, return_counts=False, axis=1),
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relax.TensorType(dtype="float32", ndim=3),
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)
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_check_inference(
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bb,
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relax.op.unique(
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x0, return_index=False, return_inverse=False, return_counts=True, axis=None
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),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=False, return_inverse=False, return_counts=True, axis=1),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(
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x0, return_index=False, return_inverse=True, return_counts=False, axis=None
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),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=False, return_inverse=True, return_counts=False, axis=1),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=False, return_inverse=True, return_counts=True, axis=None),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=False, return_inverse=True, return_counts=True, axis=1),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(
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x0, return_index=True, return_inverse=False, return_counts=False, axis=None
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),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=False, return_counts=False, axis=1),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=False, return_counts=True, axis=None),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=False, return_counts=True, axis=1),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
|
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=False, axis=None),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
|
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=False, axis=1),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
|
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=True, axis=None),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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|
relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=True, axis=1),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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_check_inference(
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bb,
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relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=True, axis=-2),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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|
_check_inference(
|
|
bb,
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relax.op.unique(
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x0, sorted=True, return_index=True, return_inverse=True, return_counts=True, axis=None
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),
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relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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|
_check_inference(
|
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bb,
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relax.op.unique(
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x0, sorted=True, return_index=True, return_inverse=True, return_counts=True, axis=1
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),
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|
relax.TupleType(
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[
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relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
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|
relax.TensorType(dtype="int64", ndim=1),
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relax.TensorType(dtype="int64", ndim=1),
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]
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),
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)
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|
_check_inference(
|
|
bb,
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|
relax.op.unique(
|
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x1, return_index=False, return_inverse=False, return_counts=False, axis=None
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),
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relax.TensorType(dtype="float32", ndim=1),
|
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)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=False, return_inverse=False, return_counts=False, axis=1),
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relax.TensorType(dtype="float32", ndim=3),
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)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
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x1, return_index=False, return_inverse=True, return_counts=False, axis=None
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),
|
|
relax.TupleType(
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|
[
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|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
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),
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|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=False, return_inverse=True, return_counts=False, axis=1),
|
|
relax.TupleType(
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|
[
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|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=False, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
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]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=False, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
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),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
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x2, return_index=False, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x2, return_index=False, return_inverse=False, return_counts=False, axis=1),
|
|
relax.TensorType(dtype="float32"),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x2, return_index=True, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TupleType(
|
|
[
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|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x2, return_index=True, return_inverse=False, return_counts=False, axis=1),
|
|
relax.TupleType(
|
|
[relax.TensorType(dtype="float32"), relax.TensorType(dtype="int64", ndim=1)]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x2, return_index=True, return_inverse=True, return_counts=False, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x2, return_index=True, return_inverse=True, return_counts=False, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32"),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x2, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x2, return_index=True, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32"),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x3, return_index=False, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TensorType(dtype="", ndim=1),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x3, return_index=False, return_inverse=False, return_counts=False, axis=1),
|
|
relax.TensorType(dtype="", ndim=3),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x3, return_index=False, return_inverse=False, return_counts=True, axis=None
|
|
),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x3, return_index=False, return_inverse=False, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x3, return_index=False, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x3, return_index=False, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x3, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x3, return_index=True, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
|
|
|
|
def test_unique_infer_ty_shape_symbolic():
|
|
bb = relax.BlockBuilder()
|
|
a = tirx.Var("a", "int64")
|
|
b = tirx.Var("b", "int64")
|
|
c = tirx.Var("c", "int64")
|
|
x = relax.Var("x", R.Tensor((a, b, c), "float32"))
|
|
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x, return_index=False, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x, return_index=False, return_inverse=False, return_counts=False, axis=1),
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x, return_index=False, return_inverse=False, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x, return_index=False, return_inverse=False, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x, return_index=False, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x, return_index=False, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x, return_index=True, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
|
|
|
|
def test_unique_infer_ty_shape_var():
|
|
bb = relax.BlockBuilder()
|
|
s0 = relax.Var("s", relax.ShapeType((2, 3, 4)))
|
|
s1 = relax.Var("s", relax.ShapeType())
|
|
x0 = relax.Var("x", relax.TensorType(s0, "float32"))
|
|
x1 = relax.Var("x", relax.TensorType(s1, "float32"))
|
|
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x0, return_index=False, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=False, return_inverse=False, return_counts=False, axis=1),
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x0, return_index=False, return_inverse=False, return_counts=True, axis=None
|
|
),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=False, return_inverse=False, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=False, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=False, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=3),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x1, return_index=False, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=False, return_inverse=False, return_counts=False, axis=1),
|
|
relax.TensorType(dtype="float32"),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x1, return_index=False, return_inverse=False, return_counts=True, axis=None
|
|
),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=False, return_inverse=False, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[relax.TensorType(dtype="float32"), relax.TensorType(dtype="int64", ndim=1)]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=False, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=False, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32"),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=True, return_counts=True, axis=1),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float32"),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
|
|
|
|
def test_unique_infer_ty_more_input_dtype():
|
|
bb = relax.BlockBuilder()
|
|
x0 = relax.Var("x", R.Tensor((2, 3, 4), "float16"))
|
|
x1 = relax.Var("x", R.Tensor((2, 3, 4), "int8"))
|
|
x2 = relax.Var("x", R.Tensor((2, 3, 4), "int32"))
|
|
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="float16", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="int8", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x2, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType(dtype="int32", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
relax.TensorType(dtype="int64", ndim=1),
|
|
]
|
|
),
|
|
)
|
|
|
|
|
|
def test_unique_infer_ty_input_zero_rank():
|
|
bb = relax.BlockBuilder()
|
|
s0 = relax.Var("s", relax.ShapeType(()))
|
|
s1 = relax.Var("s", relax.ShapeType(ndim=0))
|
|
x0 = relax.Var("x", R.Tensor((), "float32"))
|
|
x1 = relax.Var("x", R.Tensor("float32", ndim=0))
|
|
x2 = relax.Var("x", relax.TensorType(s0, "float32"))
|
|
x3 = relax.Var("x", relax.TensorType(s1, "float32"))
|
|
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x0, return_index=True, return_inverse=True, return_counts=True, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType((1,), "float32"),
|
|
relax.TensorType((1,), "int64"),
|
|
relax.TensorType((1,), "int64"),
|
|
relax.TensorType((1,), "int64"),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(x1, return_index=True, return_inverse=True, return_counts=False, axis=None),
|
|
relax.TupleType(
|
|
[
|
|
relax.TensorType((1,), "float32"),
|
|
relax.TensorType((1,), "int64"),
|
|
relax.TensorType((1,), "int64"),
|
|
]
|
|
),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x2, return_index=True, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TupleType([relax.TensorType((1,), "float32"), relax.TensorType((1,), "int64")]),
|
|
)
|
|
_check_inference(
|
|
bb,
|
|
relax.op.unique(
|
|
x3, return_index=False, return_inverse=False, return_counts=False, axis=None
|
|
),
|
|
relax.TensorType((1,), "float32"),
|
|
)
|
|
|
|
|
|
def test_unique_infer_ty_axis_out_of_range():
|
|
bb = relax.BlockBuilder()
|
|
x0 = relax.Var("x", R.Tensor((2, 3, 4), "float32"))
|
|
x1 = relax.Var("x", R.Tensor((), "float32"))
|
|
|
|
with pytest.raises(ValueError):
|
|
bb.normalize(relax.op.unique(x0, axis=3))
|
|
with pytest.raises(ValueError):
|
|
bb.normalize(relax.op.unique(x0, axis=-4))
|
|
with pytest.raises(ValueError):
|
|
bb.normalize(relax.op.unique(x1, axis=0))
|
|
|
|
|
|
def test_unique_infer_ty_wrong_input_dtype():
|
|
bb = relax.BlockBuilder()
|
|
x0 = relax.Var("x", relax.ShapeType((2, 3, 4)))
|
|
x1 = relax.Var("x", relax.FuncType([], R.Tensor((2, 3, 4), "float32")))
|
|
|
|
with pytest.raises(TypeError):
|
|
bb.normalize(relax.op.unique(x0))
|
|
with pytest.raises(TypeError):
|
|
bb.normalize(relax.op.unique(x1))
|
|
|
|
|
|
@pytest.mark.parametrize("shape", [(1,), (2, 3), (4, 5, 6)])
|
|
def test_nonzero_infer_ty(shape):
|
|
bb = relax.BlockBuilder()
|
|
x0 = relax.Var("x", R.Tensor(shape, "bool"))
|
|
|
|
_check_inference(
|
|
bb,
|
|
relax.op.nonzero(x0),
|
|
relax.TensorType(ndim=2, dtype="int64"),
|
|
)
|
|
|
|
|
|
def test_nonzero_infer_ty_ndim_zero():
|
|
bb = relax.BlockBuilder()
|
|
x = relax.Var("x", R.Tensor((), "bool"))
|
|
|
|
_check_inference(
|
|
bb,
|
|
relax.op.nonzero(x),
|
|
relax.TensorType(ndim=2, dtype="int64"),
|
|
)
|
|
|
|
|
|
def test_nonzero_infer_ty_wrong_input_dtype():
|
|
bb = relax.BlockBuilder()
|
|
x0 = relax.Var("x", relax.ShapeType((2, 3, 4)))
|
|
x1 = relax.Var("x", relax.FuncType([], R.Tensor((2, 3, 4), "float32")))
|
|
|
|
with pytest.raises(TypeError):
|
|
bb.normalize(relax.op.nonzero(x0))
|
|
with pytest.raises(TypeError):
|
|
bb.normalize(relax.op.nonzero(x1))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
tvm.testing.main()
|