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Posted to commits@tvm.apache.org by ju...@apache.org on 2022/09/17 22:55:09 UTC
[tvm] 02/02: Fix unittests
This is an automated email from the ASF dual-hosted git repository.
junrushao pushed a commit to branch ir-builder-v2
in repository https://gitbox.apache.org/repos/asf/tvm.git
commit 964f195f8ab8e9b53d4fdca7b9b5a6c6bc44eea1
Author: Junru Shao <ju...@gmail.com>
AuthorDate: Sat Sep 17 15:53:15 2022 -0700
Fix unittests
---
.../unittest/test_aot_legalize_packed_call.py | 12 ++--
.../unittest/test_meta_schedule_space_cuda.py | 5 +-
.../python/unittest/test_tir_lower_match_buffer.py | 43 +++++++------
.../test_tir_transform_inject_software_pipeline.py | 14 ++---
.../test_tir_transform_inject_virtual_thread.py | 17 +++--
.../python/unittest/test_tvmscript_error_report.py | 45 ++-----------
tests/python/unittest/test_tvmscript_spans.py | 73 ----------------------
.../python/unittest/test_tvmscript_syntax_sugar.py | 53 +++++++++-------
8 files changed, 84 insertions(+), 178 deletions(-)
diff --git a/tests/python/unittest/test_aot_legalize_packed_call.py b/tests/python/unittest/test_aot_legalize_packed_call.py
index 9c597a55e5..cd0114d464 100644
--- a/tests/python/unittest/test_aot_legalize_packed_call.py
+++ b/tests/python/unittest/test_aot_legalize_packed_call.py
@@ -15,11 +15,11 @@
# specific language governing permissions and limitations
# under the License.
# pylint: disable=missing-function-docstring,missing-module-docstring
+import pytest
import tvm
-from tvm.script import tir as T
-from tvm import tir
import tvm.testing
-import pytest
+from tvm import tir
+from tvm.script import tir as T
@tvm.script.ir_module
@@ -85,7 +85,7 @@ class Expected:
T.tvm_stack_make_shape(1, dtype="handle"),
T.reinterpret(T.uint64(0), dtype="handle"),
T.uint32(1),
- T.cast(0, dtype="float32"),
+ T.Cast("float32", 0),
0,
dtype="handle",
),
@@ -94,7 +94,7 @@ class Expected:
T.tvm_stack_make_shape(1, dtype="handle"),
T.reinterpret(T.uint64(0), dtype="handle"),
T.uint32(1),
- T.cast(0, dtype="float32"),
+ T.Cast("float32", 0),
0,
dtype="handle",
),
@@ -103,7 +103,7 @@ class Expected:
T.tvm_stack_make_shape(1, dtype="handle"),
T.reinterpret(T.uint64(0), dtype="handle"),
T.uint32(1),
- T.cast(0, dtype="float32"),
+ T.Cast("float32", 0),
0,
dtype="handle",
),
diff --git a/tests/python/unittest/test_meta_schedule_space_cuda.py b/tests/python/unittest/test_meta_schedule_space_cuda.py
index ffa2b57ba8..666170e819 100644
--- a/tests/python/unittest/test_meta_schedule_space_cuda.py
+++ b/tests/python/unittest/test_meta_schedule_space_cuda.py
@@ -15,8 +15,9 @@
# specific language governing permissions and limitations
# under the License.
"""Tests for MetaSchedule search space on CUDA"""
-from tvm import te, topi, autotvm
+from tvm import autotvm
from tvm import meta_schedule as ms
+from tvm import te, topi
from tvm.meta_schedule.testing.space_generation import check_sketches, print_sketches
from tvm.meta_schedule.testing.te_workload import create_te_workload
from tvm.script import tir as T
@@ -910,7 +911,7 @@ def test_cuda_nrm():
for i0_1 in T.thread_binding(128, thread="threadIdx.x"):
with T.block("D"):
b = T.axis.spatial(1, i0_1)
- T.where(0 * 128 + i0_1 < 1)
+ T.where(T.int32(0) * 128 + i0_1 < 1)
T.reads(C_shared[b])
T.writes(D[b])
D[b] = T.sqrt(C_shared[b], dtype="float32")
diff --git a/tests/python/unittest/test_tir_lower_match_buffer.py b/tests/python/unittest/test_tir_lower_match_buffer.py
index 93b7caf9cd..51fb28b7da 100644
--- a/tests/python/unittest/test_tir_lower_match_buffer.py
+++ b/tests/python/unittest/test_tir_lower_match_buffer.py
@@ -16,7 +16,6 @@
# under the License.
import pytest
-
import tvm
from tvm.script import tir as T
@@ -62,9 +61,17 @@ def transformed_buffer_load_store(a: T.handle, c: T.handle) -> None:
A[i * 4 + ii, j, k * 2 + kk] += C[i * 4 + ii, k * 2 + kk]
-@tvm.ir.register_op_attr("tir.intrin_test", "")
-def intrin_test(data, elem_offset, stride_0, stride_1, shape_0, shape_1):
- return 0
+def intrin_test(data, elem_offset, stride_0, stride_1, shape_0, shape_1, dtype):
+ return tvm.tir.call_intrin(
+ dtype,
+ "tir.intrin_test",
+ data,
+ elem_offset,
+ stride_0,
+ stride_1,
+ shape_0,
+ shape_1,
+ )
@T.prim_func
@@ -82,7 +89,7 @@ def opaque_access(a: T.handle, b: T.handle) -> None:
offset_factor=1,
)
T.evaluate(
- T.intrin_test(
+ intrin_test(
sub_A.data,
sub_A.elem_offset,
sub_A.strides[0],
@@ -105,7 +112,7 @@ def opaque_access(a: T.handle, b: T.handle) -> None:
offset_factor=1,
)
T.evaluate(
- T.intrin_test(
+ intrin_test(
sub_B.data,
sub_B.elem_offset,
sub_B.strides[0],
@@ -126,7 +133,7 @@ def transformed_opaque_access(a: T.handle, b: T.handle) -> None:
T.reads([])
T.writes(A[i * 16 : i * 16 + 16, j, k * 16 : k * 16 + 16])
T.evaluate(
- T.intrin_test(
+ intrin_test(
A.data,
i * 131072 + j * 128 + k * 16,
8192,
@@ -141,7 +148,7 @@ def transformed_opaque_access(a: T.handle, b: T.handle) -> None:
T.reads([])
T.writes(B[i, j * 32 : j * 32 + 32, k * 8 : k * 8 + 8])
T.evaluate(
- T.intrin_test(
+ intrin_test(
B.data,
i * 4096 + j * 2048 + k * 8,
64,
@@ -169,7 +176,7 @@ def high_dim_opaque_access(a: T.handle) -> None:
offset_factor=1,
)
T.evaluate(
- T.intrin_test(
+ intrin_test(
sub_A.data,
sub_A.elem_offset,
sub_A.strides[0],
@@ -189,7 +196,7 @@ def transformed_high_dim_opaque_access(a: T.handle) -> None:
T.reads([])
T.writes(A[i, j * 16 : j * 16 + 16, k * 16 : k * 16 + 16])
T.evaluate(
- T.intrin_test(
+ intrin_test(
A.data,
i * 2048 + j * 1024 + k * 16,
64,
@@ -217,7 +224,7 @@ def high_dim_opaque_access_with_source_strides(a: T.handle) -> None:
offset_factor=1,
)
T.evaluate(
- T.intrin_test(
+ intrin_test(
sub_A.data,
sub_A.elem_offset,
sub_A.strides[0],
@@ -237,7 +244,7 @@ def transformed_high_dim_opaque_access_with_source_strides(a: T.handle) -> None:
T.reads([])
T.writes(A[i, j * 16 : j * 16 + 16, k * 16 : k * 16 + 16])
T.evaluate(
- T.intrin_test(
+ intrin_test(
A.data,
i * 2576 + j * 1280 + k * 16,
80,
@@ -298,7 +305,7 @@ def recursive_match(a: T.handle, b: T.handle) -> None:
offset_factor=1,
)
T.evaluate(
- T.intrin_test(
+ intrin_test(
sub_sub_A.data,
sub_sub_A.elem_offset,
sub_sub_A.strides[0],
@@ -343,7 +350,7 @@ def transformed_recursive_match(a: T.handle, b: T.handle) -> None:
]
)
T.evaluate(
- T.intrin_test(
+ intrin_test(
A.data,
i * 4096 + j * 1024 + jj * 256 + k * 16 + kk * 4,
64,
@@ -375,7 +382,7 @@ def symbolic_match(a: T.handle, b: T.handle, n: T.int32, m: T.int32) -> None:
sub_A[ii, jj] = 1
for j in range(0, 4):
T.evaluate(
- T.intrin_test(
+ intrin_test(
sub_B.data,
sub_B.elem_offset,
sub_B.strides[0],
@@ -399,7 +406,7 @@ def transformed_symbolic_match(a: T.handle, b: T.handle, n: T.int32, m: T.int32)
A[i * m + ii, jj] = 1
for j in range(0, 4):
T.evaluate(
- T.intrin_test(
+ intrin_test(
B.data,
i * n * (m * 4),
m * 4,
@@ -423,7 +430,7 @@ def rank0_buffer(a: T.handle, b: T.handle) -> None:
sub_B = T.match_buffer(B[i, j], (), offset_factor=1)
sub_A[()] = 1
T.evaluate(
- T.intrin_test(
+ intrin_test(
sub_B.data,
sub_B.elem_offset,
0,
@@ -445,7 +452,7 @@ def transformed_rank0_buffer(a: T.handle, b: T.handle) -> None:
T.writes([A[i, j], B[i, j]])
A[i, j] = 1
T.evaluate(
- T.intrin_test(
+ intrin_test(
B.data,
i * 8 + j,
0,
diff --git a/tests/python/unittest/test_tir_transform_inject_software_pipeline.py b/tests/python/unittest/test_tir_transform_inject_software_pipeline.py
index edaeb7c9b6..34f988c77c 100644
--- a/tests/python/unittest/test_tir_transform_inject_software_pipeline.py
+++ b/tests/python/unittest/test_tir_transform_inject_software_pipeline.py
@@ -14,16 +14,16 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
-import pytest
import sys
-import numpy as np
+import numpy as np
+import pytest
import tvm
import tvm.testing
import tvm.tir.tensor_intrin.cuda
-from tvm import tir, te, TVMError
-from tvm.script import tir as T
+from tvm import TVMError, te, tir
from tvm.meta_schedule.testing import te_workload
+from tvm.script import tir as T
from tvm.testing.tir import mma_schedule
from tvm.tir.tensor_intrin.cuda import (
LDMATRIX_16x16_A_DYN_INTRIN,
@@ -1060,7 +1060,7 @@ def test_simple_compute_async():
T.writes(B[0, tx, 0])
with T.attr(0, "async_commit_queue_scope", 0):
with T.attr(0, "async_scope", 1):
- B[0 % 2, tx, 0] = A[tx, 0] * T.float32(2)
+ B[T.int32(0) % 2, tx, 0] = A[tx, 0] * T.float32(2)
with T.block():
T.reads(A[tx, 1:16], B[0:2, tx, 0])
T.writes(B[0:2, tx, 0], C[tx, 0:15])
@@ -1080,11 +1080,11 @@ def test_simple_compute_async():
with T.attr(0, "async_wait_inflight_count", 1):
C[tx, i - 1 + 1] = B[(i - 1 + 1) % 2, tx, 0] + T.float32(1)
with T.block():
- T.reads(B[15 % 2, tx, 0])
+ T.reads(B[T.int32(15) % 2, tx, 0])
T.writes(C[tx, 15])
with T.attr(0, "async_wait_queue_scope", 0):
with T.attr(0, "async_wait_inflight_count", 0):
- C[tx, 15] = B[15 % 2, tx, 0] + T.float32(1)
+ C[tx, 15] = B[T.int32(15) % 2, tx, 0] + T.float32(1)
tvm.ir.assert_structural_equal(mod["main"], ref, True)
diff --git a/tests/python/unittest/test_tir_transform_inject_virtual_thread.py b/tests/python/unittest/test_tir_transform_inject_virtual_thread.py
index 548f3bc8d1..6000ea339b 100644
--- a/tests/python/unittest/test_tir_transform_inject_virtual_thread.py
+++ b/tests/python/unittest/test_tir_transform_inject_virtual_thread.py
@@ -16,7 +16,6 @@
# under the License.
import tvm
from tvm import te
-
from tvm.script import tir as T
vthread_name = tvm.testing.parameter("vthread", "cthread")
@@ -155,10 +154,10 @@ def test_vthread_simplified():
B = T.buffer_decl([16], "int32", data=B_data, scope="shared")
# The indices for B should each be a single Ramp node, and
# should not be the sum of a Ramp and Broadcast node.
- B[0 * 4 : 0 * 4 + 4] = T.broadcast(0, 4)
- B[1 * 4 : 1 * 4 + 4] = T.broadcast(1, 4)
- B[2 * 4 : 2 * 4 + 4] = T.broadcast(2, 4)
- B[3 * 4 : 3 * 4 + 4] = T.broadcast(3, 4)
+ B[T.int32(0) * 4 : T.int32(0) * 4 + 4] = T.broadcast(0, 4)
+ B[T.int32(1) * 4 : T.int32(1) * 4 + 4] = T.broadcast(1, 4)
+ B[T.int32(2) * 4 : T.int32(2) * 4 + 4] = T.broadcast(2, 4)
+ B[T.int32(3) * 4 : T.int32(3) * 4 + 4] = T.broadcast(3, 4)
before_mod = tvm.IRModule.from_expr(before_func)
after_mod = tvm.tir.transform.InjectVirtualThread()(before_mod)
@@ -182,10 +181,10 @@ def test_vthread_vectorized():
def expected_func():
B_data = T.allocate([4], "int32x4", "shared")
B = T.buffer_decl([4], "int32x4", data=B_data, scope="shared")
- B[0 * 4 / 4] = T.broadcast(0, 4)
- B[1 * 4 / 4] = T.broadcast(1, 4)
- B[2 * 4 / 4] = T.broadcast(2, 4)
- B[3 * 4 / 4] = T.broadcast(3, 4)
+ B[T.int32(0) * 4 / 4] = T.broadcast(0, 4)
+ B[T.int32(1) * 4 / 4] = T.broadcast(1, 4)
+ B[T.int32(2) * 4 / 4] = T.broadcast(2, 4)
+ B[T.int32(3) * 4 / 4] = T.broadcast(3, 4)
before_mod = tvm.IRModule.from_expr(before_func)
intermediate_mod = tvm.tir.transform.InjectVirtualThread()(before_mod)
diff --git a/tests/python/unittest/test_tvmscript_error_report.py b/tests/python/unittest/test_tvmscript_error_report.py
index acc68af065..7d27eac4e9 100644
--- a/tests/python/unittest/test_tvmscript_error_report.py
+++ b/tests/python/unittest/test_tvmscript_error_report.py
@@ -15,12 +15,13 @@
# specific language governing permissions and limitations
# under the License.
-import pytest
import sys
+
+import pytest
import tvm
from tvm import tir
-from tvm.testing import check_error
from tvm.script import tir as T
+from tvm.testing import check_error
def buffer_bind_missing_args(a: T.handle) -> None:
@@ -76,14 +77,6 @@ def test_missing_type_annotation():
check_error(missing_type_annotation, 1)
-def invalid_expr_stmt() -> None:
- T.max(1, 2) # error
-
-
-def test_invalid_expr_stmt():
- check_error(invalid_expr_stmt, 2)
-
-
def invalid_for_function(a: T.handle) -> None:
A = T.match_buffer(a, (16, 16), "float32")
@@ -115,14 +108,6 @@ def test_return_not_allowed():
check_error(return_not_allowed, 2)
-def tir_assert(a: T.handle) -> None:
- T.Assert(0, "") # error
-
-
-def test_tir_assert():
- check_error(tir_assert, 2)
-
-
def no_body(a: T.handle) -> None:
A = T.match_buffer(a, (16, 16), "float32")
T.realize(A, "") # error
@@ -250,19 +235,6 @@ def test_invalid_match_buffer_region():
check_error(invalid_match_buffer_region, 5)
-def duplicate_buffer() -> None:
- A = T.alloc_buffer((128, 128), "float32")
- for i, j in T.grid(128, 128):
- with T.block():
- vi, vj = T.axis.remap("SS", [i, j])
- A = T.alloc_buffer((128, 128), "float32") # error
- T.evaluate(1.0)
-
-
-def test_duplicate_buffer():
- check_error(duplicate_buffer, 6)
-
-
def duplicate_reads() -> None:
A = T.alloc_buffer((128, 128), "float32")
for i, j in T.grid(128, 128):
@@ -334,7 +306,7 @@ def opaque_access_during_complete(a: T.handle) -> None: # error
def test_opaque_access_during_complete():
- check_error(opaque_access_during_complete, 1)
+ check_error(opaque_access_during_complete, 0)
def convert_slice_to_bufferload() -> None:
@@ -608,15 +580,6 @@ def test_binop_bad_type():
check_error(binop_bad_type, 3)
-def floor_dtype(h: T.handle):
- h_ = T.match_buffer(h, [1])
- h_[0] = T.floor(2) # error floor requires a dtype
-
-
-def test_floor_dtype():
- check_error(floor_dtype, 3)
-
-
def non_integer_typed_block_iter():
with T.block():
i = T.axis.S(0.1, 0.1) # error IterVar requires an integer dtype
diff --git a/tests/python/unittest/test_tvmscript_spans.py b/tests/python/unittest/test_tvmscript_spans.py
deleted file mode 100644
index f863a4dd98..0000000000
--- a/tests/python/unittest/test_tvmscript_spans.py
+++ /dev/null
@@ -1,73 +0,0 @@
-# Licensed to the Apache Software Foundation (ASF) under one
-# or more contributor license agreements. See the NOTICE file
-# distributed with this work for additional information
-# regarding copyright ownership. The ASF licenses this file
-# to you under the Apache License, Version 2.0 (the
-# "License"); you may not use this file except in compliance
-# with the License. You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing,
-# software distributed under the License is distributed on an
-# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-# KIND, either express or implied. See the License for the
-# specific language governing permissions and limitations
-# under the License.
-
-
-from tvm.script import tir as T
-
-
-@T.prim_func
-def loops() -> None:
- for i in T.parallel(0, 2):
- for j in T.serial(0, 1):
- for z in T.vectorized(3, 4):
- T.evaluate(0)
-
-
-def test_loops():
- start_line = 23
- parsed = loops
-
- assert parsed.span.line == start_line
-
- assert parsed.body.span.line == start_line + 1
- assert parsed.body.min.span.column == 25
- assert parsed.body.extent.span.column == 28
- assert parsed.body.extent.span.line == start_line + 1
-
- assert parsed.body.body.span.line == start_line + 2
- assert parsed.body.body.loop_var.span.line == start_line + 2
- assert parsed.body.body.loop_var.span.column == 13
-
- assert parsed.body.body.body.span.line == start_line + 3
- assert parsed.body.body.body.span.column == 22
-
- assert parsed.body.body.body.body.span.line == start_line + 4
- assert parsed.body.body.body.body.span.column == 17
-
-
-@T.prim_func
-def statements() -> None:
- T.evaluate(1)
- T.evaluate("test")
-
-
-def test_statements():
- start_line = 53
- parsed = statements
-
- assert parsed.body.span.line == start_line + 1
-
- assert parsed.body[0].span.line == start_line + 1
- assert parsed.body[0].span.column == 5
-
- assert parsed.body[0].span.line == start_line + 1
- assert parsed.body[0].span.column == 5
-
-
-if __name__ == "__main__":
- test_loops()
- test_statements()
diff --git a/tests/python/unittest/test_tvmscript_syntax_sugar.py b/tests/python/unittest/test_tvmscript_syntax_sugar.py
index d955ec0a8c..d09a0d143a 100644
--- a/tests/python/unittest/test_tvmscript_syntax_sugar.py
+++ b/tests/python/unittest/test_tvmscript_syntax_sugar.py
@@ -20,8 +20,8 @@ import sys
import pytest
import tvm.testing
from tvm.ir import assert_structural_equal
+from tvm.script import from_source
from tvm.script import tir as T
-from tvm.script.parser import from_source
from tvm.testing import check_error
@@ -164,15 +164,24 @@ def test_match_buffer_1d():
# match buffer failed case
-def test_match_buffer_no_kwargs_failed():
- with pytest.raises(ValueError) as e:
-
- @T.prim_func
- def elementwise_buffer_no_kwargs_failed(
- a: T.Buffer[(128, 128, 128, 128)],
- b: T.Buffer[(128, 128, 128, 128)],
- ) -> None:
- pass
+def test_match_buffer_without_dtype():
+ @T.prim_func
+ def no_dtype(
+ a: T.Buffer[(128, 128, 128, 128)],
+ b: T.Buffer[(128, 128, 128, 128)],
+ ) -> None:
+ pass
+
+ a0, a1, a2, a3 = no_dtype.buffer_map[no_dtype.params[0]].shape
+ b0, b1, b2, b3 = no_dtype.buffer_map[no_dtype.params[1]].shape
+ assert a0 == 128
+ assert a1 == 128
+ assert a2 == 128
+ assert a3 == 128
+ assert b0 == 128
+ assert b1 == 128
+ assert b2 == 128
+ assert b3 == 128
# dynamic shape gemm
@@ -274,8 +283,8 @@ def test_letstmt_bind_with_constant():
@T.prim_func
def constant_binds_wrapped():
- x = T.int32(1)
- y = T.float32(42.0)
+ x = T.inline(T.int32(1))
+ y = T.inline(T.float32(42.0))
T.evaluate(T.cast(x, "float32") + y)
assert_structural_equal(constant_binds, constant_binds_wrapped)
@@ -288,9 +297,9 @@ def test_func_call():
@T.prim_func
def mma_sync_m16n16k16_desc(a: T.handle, b: T.handle, c: T.handle) -> None:
- A = T.match_buffer(a, (32, 8), "float16", align=64, offset_factor=16, scope="warp")
- B = T.match_buffer(b, (32, 8), "float16", align=64, offset_factor=16, scope="warp")
- C = T.match_buffer(c, (32, 8), "float16", align=64, offset_factor=16, scope="warp")
+ A = T.match_buffer(a, (32, 8), "float16", align=128, offset_factor=16, scope="warp")
+ B = T.match_buffer(b, (32, 8), "float16", align=128, offset_factor=16, scope="warp")
+ C = T.match_buffer(c, (32, 8), "float16", align=128, offset_factor=16, scope="warp")
with T.block("root"):
T.reads(C[0:32, 0:8], A[0:32, 0:8], B[0:32, 0:8])
@@ -298,9 +307,9 @@ def test_func_call():
for i, j, k in T.grid(16, 16, 16):
with T.block("C"):
i, j, k = T.axis.remap("SSR", [i, j, k])
- thread_id_C, local_id_C = shared_16x16_to_ldmatrix_32x8_layout(i, j)
- thread_id_A, local_id_A = shared_16x16_to_ldmatrix_32x8_layout(i, k)
- thread_id_B, local_id_B = shared_16x16_to_ldmatrix_32x8_layout(k, j)
+ thread_id_C, local_id_C = T.inline(shared_16x16_to_ldmatrix_32x8_layout(i, j))
+ thread_id_A, local_id_A = T.inline(shared_16x16_to_ldmatrix_32x8_layout(i, k))
+ thread_id_B, local_id_B = T.inline(shared_16x16_to_ldmatrix_32x8_layout(k, j))
T.reads(
C[thread_id_C, local_id_C],
@@ -315,9 +324,9 @@ def test_func_call():
@T.prim_func
def mma_sync_m16n16k16_desc_manual(a: T.handle, b: T.handle, c: T.handle) -> None:
- A = T.match_buffer(a, (32, 8), "float16", align=64, offset_factor=16, scope="warp")
- B = T.match_buffer(b, (32, 8), "float16", align=64, offset_factor=16, scope="warp")
- C = T.match_buffer(c, (32, 8), "float16", align=64, offset_factor=16, scope="warp")
+ A = T.match_buffer(a, (32, 8), "float16", align=128, offset_factor=16, scope="warp")
+ B = T.match_buffer(b, (32, 8), "float16", align=128, offset_factor=16, scope="warp")
+ C = T.match_buffer(c, (32, 8), "float16", align=128, offset_factor=16, scope="warp")
with T.block("root"):
T.reads(C[0:32, 0:8], A[0:32, 0:8], B[0:32, 0:8])
@@ -341,7 +350,7 @@ def test_func_call():
# The following is an example of an error message from calling an invalid function
- # error: Error occurred when invoking the function sqrt:
+ # error: Error occured when invoking the function sqrt:
# loop of ufunc does not support argument 0 of type Var which has no callable sqrt method
# --> test_tvmscript_syntax_sugar.py:334:19
# |