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Posted to commits@tvm.apache.org by ma...@apache.org on 2022/12/15 01:50:29 UTC
[tvm] branch main updated: [Hexagon] Switch from default_rng to random in Hexagon tests (#13616)
This is an automated email from the ASF dual-hosted git repository.
masahi pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/tvm.git
The following commit(s) were added to refs/heads/main by this push:
new 795945be4e [Hexagon] Switch from default_rng to random in Hexagon tests (#13616)
795945be4e is described below
commit 795945be4e7532ff9a5e475dc118ee33ee086495
Author: Krzysztof Parzyszek <kp...@quicinc.com>
AuthorDate: Wed Dec 14 19:50:23 2022 -0600
[Hexagon] Switch from default_rng to random in Hexagon tests (#13616)
default_rng was introduced in numpy 1.19, which is not present
even in Ubuntu 20.04 (it comes with 1.17.4).
---
tests/python/contrib/test_hexagon/test_parallel_hvx.py | 6 ++----
tests/python/contrib/test_hexagon/test_parallel_hvx_load_vtcm.py | 5 ++---
tests/python/contrib/test_hexagon/test_parallel_scalar.py | 8 ++++----
tests/python/contrib/test_hexagon/test_vtcm_bandwidth.py | 4 +---
4 files changed, 9 insertions(+), 14 deletions(-)
diff --git a/tests/python/contrib/test_hexagon/test_parallel_hvx.py b/tests/python/contrib/test_hexagon/test_parallel_hvx.py
index 15273afdd4..13ad36278b 100644
--- a/tests/python/contrib/test_hexagon/test_parallel_hvx.py
+++ b/tests/python/contrib/test_hexagon/test_parallel_hvx.py
@@ -19,7 +19,6 @@
Test parallelizing HVX workloads and compare them to single thread examples.
"""
import numpy as np
-from numpy.random import default_rng
import tvm
from tvm.script import tir as T
@@ -148,9 +147,8 @@ def evaluate(hexagon_session, shape_dtypes, expected_output_producer, sch):
func_tir = tvm.build(sch.mod["main"], target=get_hexagon_target("v68"))
module = hexagon_session.load_module(func_tir)
- rng = default_rng()
- a = rng.integers(0, 16, a_shape, dtype=a_dtype)
- b = rng.integers(0, 16, b_shape, dtype=b_dtype)
+ a = np.random.randint(0, 16, a_shape, dtype=a_dtype)
+ b = np.random.randint(0, 16, b_shape, dtype=b_dtype)
c = np.zeros(c_shape, dtype=c_dtype)
a_hexagon = tvm.runtime.ndarray.array(a, device=hexagon_session.device)
diff --git a/tests/python/contrib/test_hexagon/test_parallel_hvx_load_vtcm.py b/tests/python/contrib/test_hexagon/test_parallel_hvx_load_vtcm.py
index 6cca44388d..ee7f789ed1 100644
--- a/tests/python/contrib/test_hexagon/test_parallel_hvx_load_vtcm.py
+++ b/tests/python/contrib/test_hexagon/test_parallel_hvx_load_vtcm.py
@@ -19,7 +19,6 @@
import numpy as np
import tvm
-from numpy.random import default_rng
from tvm.script import tir as T
from .infrastructure import get_hexagon_target
@@ -395,11 +394,11 @@ class TestMatMulVec:
@tvm.testing.fixture
def input_a(self, operations):
- return default_rng().integers(0, 16, (operations, 128), dtype="uint8")
+ return np.random.randint(0, 16, (operations, 128), dtype="uint8")
@tvm.testing.fixture
def input_b(self, operations):
- return default_rng().integers(0, 16, (operations, 128), dtype="uint8")
+ return np.random.randint(0, 16, (operations, 128), dtype="uint8")
@tvm.testing.fixture
def input_c(self, operations):
diff --git a/tests/python/contrib/test_hexagon/test_parallel_scalar.py b/tests/python/contrib/test_hexagon/test_parallel_scalar.py
index b96265d9df..0ca8c6ba0c 100644
--- a/tests/python/contrib/test_hexagon/test_parallel_scalar.py
+++ b/tests/python/contrib/test_hexagon/test_parallel_scalar.py
@@ -18,7 +18,6 @@
""" Test parallelism for multiple different scalar workloads. """
import numpy as np
-from numpy.random import default_rng
import tvm
from tvm.script import tir as T
@@ -91,9 +90,10 @@ def evaluate(hexagon_session, operations, expected, sch):
func_tir = tvm.build(sch.mod["main"], target=get_hexagon_target("v68"))
module = hexagon_session.load_module(func_tir)
- rng = default_rng()
- a = rng.random(shape, dtype=dtype)
- b = rng.random(shape, dtype=dtype)
+ # np.random.random returns float64 by default, but make the cast explicit
+ # to make it easier to switch when necessary.
+ a = np.random.random(shape).astype(dtype)
+ b = np.random.random(shape).astype(dtype)
c = np.zeros(shape, dtype=dtype)
a_hexagon = tvm.runtime.ndarray.array(a, device=hexagon_session.device)
diff --git a/tests/python/contrib/test_hexagon/test_vtcm_bandwidth.py b/tests/python/contrib/test_hexagon/test_vtcm_bandwidth.py
index 0b6b52335c..254eb00cb2 100644
--- a/tests/python/contrib/test_hexagon/test_vtcm_bandwidth.py
+++ b/tests/python/contrib/test_hexagon/test_vtcm_bandwidth.py
@@ -18,7 +18,6 @@
"""Test theoretical bandwith for data transfers to VTCM for different strategies."""
import numpy as np
-from numpy.random import default_rng
import tvm
from tvm.script import tir as T
@@ -96,8 +95,7 @@ def evaluate(hexagon_session, sch, size):
func_tir = tvm.build(sch.mod["main"], target=get_hexagon_target("v69"))
module = hexagon_session.load_module(func_tir)
- rng = default_rng()
- a = rng.integers(-128, 127, a_shape, dtype="int8")
+ a = np.random.randint(-128, 127, a_shape, dtype="int8")
a_vtcm = np.zeros(a_shape, dtype="int8")
a_hexagon = tvm.runtime.ndarray.array(a, device=hexagon_session.device, mem_scope="global")