From 5c3b2e931f34b376171a2dbf0eef2d7878f9500f Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 13:04:30 +0800 Subject: [PATCH 01/15] Create check_op_perf.py --- tools/check_op_perf.py | 82 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 82 insertions(+) create mode 100644 tools/check_op_perf.py diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py new file mode 100644 index 000000000..7b1f6ba02 --- /dev/null +++ b/tools/check_op_perf.py @@ -0,0 +1,82 @@ +import re +import os +import glob +import subprocess +from addict import Dict +from pathlib import Path + + +def find_pytorch_dir(): + path = Path(__file__).resolve() + while path != path.root: + if path.name == "pytorch": + return str(path) + path = path.parent + return '' + + +OP_LIST = { + # 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], + # 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], + 'batch_norm_1d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], + 'batch_norm_2d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], + 'batch_norm_3d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], +} + + +def find_op_time(text, ops): + res = [] + def transform_to_us(time): + if time.endswith('us'): + return float(time[:-2]) + elif time.endswith('ms'): + return float(time[:-2]) * 1000.0 + elif time.endswith('s'): + return float(time[:-1]) * 1000000.0 + else: + raise Exception("time format not support") + flag = "None" + for line in text.split('\n'): + line = line.strip() + if line.startswith('shape:'): + flag = line + for op in ops: + if op in line: + items = [] + for item in line.strip().split(' '): + if len(item) > 1: + items.append(item.strip()) + op_name = items[0] + op_time = transform_to_us(items[-2]) + res.append([op_name, flag, str(op_time)]) + res_ = ["@@".join(item) for item in res] + res_ = list(set(res_)) + res = [item.split("@@") for item in res_] + res = sorted(res, key=lambda x: x[1]) + res = sorted(res, key=lambda x: x[0]) + return res + + +if __name__ == '__main__': + root_folder = find_pytorch_dir().strip() + perf_suit = os.path.join(root_folder, 'third_party/torch-xpu-ops/test/microbench/') + import csv + csv_data = [ + ["Operator", "Tag", "Latency(us)"], + ] + for item, ops in OP_LIST.items(): + print(item) + f = os.path.join(perf_suit, item) + result = subprocess.run( + ["python", f], + capture_output=True, + text=True + ) + output = result.stdout + res = find_op_time(output, ops) + csv_data += res + for item in res: + print(item) + with open("check_op_perf.csv", mode="w", newline="", encoding="utf-8") as file: + writer = csv.writer(file) + writer.writerows(csv_data) From 32c44dc590e45e4dd3ec39c28344458c1c58d312 Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 13:22:34 +0800 Subject: [PATCH 02/15] Update check_op_perf.py --- tools/check_op_perf.py | 1 + 1 file changed, 1 insertion(+) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index 7b1f6ba02..525c1d534 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -26,6 +26,7 @@ def find_pytorch_dir(): def find_op_time(text, ops): res = [] + def transform_to_us(time): if time.endswith('us'): return float(time[:-2]) From b91b8ac946cee05dde166e646e1c7ecc0536d3ba Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 13:39:21 +0800 Subject: [PATCH 03/15] Update check_op_perf.py --- tools/check_op_perf.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index 525c1d534..c3976d7c5 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -1,8 +1,5 @@ -import re import os -import glob import subprocess -from addict import Dict from pathlib import Path From 6d4dfadccd201f1c45fe3ab798d6a41f6891f4c8 Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 14:22:49 +0800 Subject: [PATCH 04/15] Update layer_norm.py --- test/microbench/layer_norm.py | 17 ++++++++++++++--- 1 file changed, 14 insertions(+), 3 deletions(-) diff --git a/test/microbench/layer_norm.py b/test/microbench/layer_norm.py index 9262a8a8c..639524129 100644 --- a/test/microbench/layer_norm.py +++ b/test/microbench/layer_norm.py @@ -1,9 +1,20 @@ import torch from torch.profiler import profile, ProfilerActivity -device = "xpu" + +if torch.cuda.is_available(): + device = "cuda" + activity = ProfilerActivity.CUDA + table_key = "cuda_time_total" +else: + device = "xpu" + activity = ProfilerActivity.XPU + table_key = "xpu_time_total" + + backward = True + shape_list = [ ((1, 1024), (1024)), ((2, 4096, 320), (4096, 320)), @@ -38,7 +49,7 @@ backward, ) with profile( - activities=[ProfilerActivity.CPU, ProfilerActivity.XPU], record_shapes=True + activities=[ProfilerActivity.CPU, activity], record_shapes=True ) as prof: for i in range(20): m = torch.nn.LayerNorm(shape[1], device=device, dtype=dtype) @@ -46,4 +57,4 @@ if backward: gy = torch.empty_like(output) output.backward(gy) - print(prof.key_averages().table(sort_by="xpu_time_total")) + print(prof.key_averages().table(sort_by=table_key)) From 321d5956917bd9a5839ceaad777d03b9b6c762b4 Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 14:24:52 +0800 Subject: [PATCH 05/15] Update group_norm.py to support cuda --- test/microbench/group_norm.py | 17 ++++++++++++++--- 1 file changed, 14 insertions(+), 3 deletions(-) diff --git a/test/microbench/group_norm.py b/test/microbench/group_norm.py index 4a6b471a6..252805bcd 100644 --- a/test/microbench/group_norm.py +++ b/test/microbench/group_norm.py @@ -1,9 +1,20 @@ import torch from torch.profiler import profile, ProfilerActivity -device = "xpu" + +if torch.cuda.is_available(): + device = "cuda" + activity = ProfilerActivity.CUDA + table_key = "cuda_time_total" +else: + device = "xpu" + activity = ProfilerActivity.XPU + table_key = "xpu_time_total" + + backward = True + shape_list = [ (1, 32, 128, 32, 32), # all channel for 1 group (16, 1024, 128, 32, 32), # normal shape, big memory @@ -64,7 +75,7 @@ backward, ) with profile( - activities=[ProfilerActivity.CPU, ProfilerActivity.XPU], + activities=[ProfilerActivity.CPU, activity], record_shapes=True, ) as prof: for i in range(20): @@ -73,4 +84,4 @@ if backward: grad_out = torch.randn_like(output).to(device) (grad_dpcpp,) = torch.autograd.grad(output, input, grad_out) - print(prof.key_averages().table(sort_by="xpu_time_total")) + print(prof.key_averages().table(sort_by=table_key)) From 83e0f8cb0c800824c747d2eebfcd4d5092afa8b2 Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 14:26:39 +0800 Subject: [PATCH 06/15] Update batch_norm_1d.py to support cuda --- test/microbench/batch_norm_1d.py | 15 ++++++++++++--- 1 file changed, 12 insertions(+), 3 deletions(-) diff --git a/test/microbench/batch_norm_1d.py b/test/microbench/batch_norm_1d.py index 1a9bed77e..86aa5f386 100644 --- a/test/microbench/batch_norm_1d.py +++ b/test/microbench/batch_norm_1d.py @@ -1,7 +1,16 @@ import torch from torch.profiler import profile, ProfilerActivity -device = "xpu" + +if torch.cuda.is_available(): + device = "cuda" + activity = ProfilerActivity.CUDA + table_key = "cuda_time_total" +else: + device = "xpu" + activity = ProfilerActivity.XPU + table_key = "xpu_time_total" + shape_list = [((64, 8), (8)), ((4, 128, 15000), (128)), ((4, 256, 512), (256))] @@ -29,7 +38,7 @@ backward, ) with profile( - activities=[ProfilerActivity.CPU, ProfilerActivity.XPU], record_shapes=True + activities=[ProfilerActivity.CPU, activity], record_shapes=True ) as prof: for i in range(20): m = torch.nn.BatchNorm1d(shape[1], device=device) @@ -37,4 +46,4 @@ if backward: gy = torch.empty_like(output) output.backward(gy) - print(prof.key_averages().table(sort_by="xpu_time_total")) + print(prof.key_averages().table(sort_by=table_key)) From ae16d38ed67f494415aa966f70a0971e7c0383b9 Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 14:28:23 +0800 Subject: [PATCH 07/15] Update batch_norm_2d.py to support cuda --- test/microbench/batch_norm_2d.py | 21 +++++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) diff --git a/test/microbench/batch_norm_2d.py b/test/microbench/batch_norm_2d.py index 1130e6209..0abe5e5dc 100644 --- a/test/microbench/batch_norm_2d.py +++ b/test/microbench/batch_norm_2d.py @@ -1,7 +1,16 @@ import torch from torch.profiler import profile, ProfilerActivity -device = "xpu" + +if torch.cuda.is_available(): + device = "cuda" + activity = ProfilerActivity.CUDA + table_key = "cuda_time_total" +else: + device = "xpu" + activity = ProfilerActivity.XPU + table_key = "xpu_time_total" + shape_list = [ (256, 256, 56, 56, 256), @@ -20,14 +29,14 @@ def BTN2d(shape, dtype, channels_last, backward): input = ( torch.randn(N, C, H, W) .to(memory_format=torch.channels_last) - .to(device="xpu", dtype=dtype) + .to(device=device, dtype=dtype) ) else: - input = torch.randn(N, C, H, W).to(device="xpu", dtype=dtype) + input = torch.randn(N, C, H, W).to(device=device, dtype=dtype) if backward: input.requires_grad_(True) - grad = torch.randn([C, H, W]).to(device="xpu", dtype=dtype) + grad = torch.randn([C, H, W]).to(device=device, dtype=dtype) BTN = torch.nn.BatchNorm2d(shape[4], device=device) @@ -59,9 +68,9 @@ def BTN2d(shape, dtype, channels_last, backward): backward, ) with profile( - activities=[ProfilerActivity.CPU, ProfilerActivity.XPU], + activities=[ProfilerActivity.CPU, activity], record_shapes=True, ) as prof: for i in range(20): BTN2d(shape, dtype, channels_last, backward=True) - print(prof.key_averages().table(sort_by="xpu_time_total")) + print(prof.key_averages().table(sort_by=table_key)) From ca1eac11c3558a465e7fff76d28104fe54745a6f Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 14:29:37 +0800 Subject: [PATCH 08/15] Update batch_norm_3d.py to support cuda --- test/microbench/batch_norm_3d.py | 21 +++++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) diff --git a/test/microbench/batch_norm_3d.py b/test/microbench/batch_norm_3d.py index 5bf376574..bb94ba172 100644 --- a/test/microbench/batch_norm_3d.py +++ b/test/microbench/batch_norm_3d.py @@ -1,7 +1,16 @@ import torch from torch.profiler import profile, ProfilerActivity -device = "xpu" + +if torch.cuda.is_available(): + device = "cuda" + activity = ProfilerActivity.CUDA + table_key = "cuda_time_total" +else: + device = "xpu" + activity = ProfilerActivity.XPU + table_key = "xpu_time_total" + shape_list = [(2, 5, 6, 3, 5, 5), (2, 8, 64, 64, 64, 8), (16, 16, 128, 128, 256, 16)] @@ -20,14 +29,14 @@ def BTN3d(shape, dtype, channels_last, backward): input = ( torch.randn(N, C, D, H, W) .to(memory_format=torch.channels_last_3d) - .to(device="xpu", dtype=dtype) + .to(device=device, dtype=dtype) ) else: - input = torch.randn(N, C, D, H, W).to(device="xpu", dtype=dtype) + input = torch.randn(N, C, D, H, W).to(device=device, dtype=dtype) if backward: input.requires_grad_(True) - grad = torch.randn([C, D, H, W]).to(device="xpu", dtype=dtype) + grad = torch.randn([C, D, H, W]).to(device=device, dtype=dtype) BTN = torch.nn.BatchNorm3d(shape[5], device=device) @@ -59,9 +68,9 @@ def BTN3d(shape, dtype, channels_last, backward): backward, ) with profile( - activities=[ProfilerActivity.CPU, ProfilerActivity.XPU], + activities=[ProfilerActivity.CPU, activity], record_shapes=True, ) as prof: for i in range(20): BTN3d(shape, dtype, channels_last, backward=True) - print(prof.key_averages().table(sort_by="xpu_time_total")) + print(prof.key_averages().table(sort_by=table_key)) From ec116b08a53c9cd51f524dc6158b4b90dfb87f27 Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 14:31:29 +0800 Subject: [PATCH 09/15] Update check_op_perf.py --- tools/check_op_perf.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index c3976d7c5..2ef0990ba 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -13,8 +13,8 @@ def find_pytorch_dir(): OP_LIST = { - # 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], - # 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], + 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], + 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], 'batch_norm_1d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], 'batch_norm_2d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], 'batch_norm_3d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], From b141de93de4422b0551817a7680d121a00cd623f Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Fri, 9 May 2025 15:27:31 +0800 Subject: [PATCH 10/15] Update check_op_perf.py --- tools/check_op_perf.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index 2ef0990ba..f7ece59aa 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -6,7 +6,7 @@ def find_pytorch_dir(): path = Path(__file__).resolve() while path != path.root: - if path.name == "pytorch": + if path.name == "torch-xpu-ops": return str(path) path = path.parent return '' @@ -57,7 +57,7 @@ def transform_to_us(time): if __name__ == '__main__': root_folder = find_pytorch_dir().strip() - perf_suit = os.path.join(root_folder, 'third_party/torch-xpu-ops/test/microbench/') + perf_suit = os.path.join(root_folder, 'test/microbench/') import csv csv_data = [ ["Operator", "Tag", "Latency(us)"], From aa90efe8e1abb9249f70213ddbd9f9ae51fc20ea Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Tue, 13 May 2025 16:02:33 +0800 Subject: [PATCH 11/15] Update check_op_perf.py --- tools/check_op_perf.py | 38 +++++++++++++++++++++++++------------- 1 file changed, 25 insertions(+), 13 deletions(-) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index f7ece59aa..c78482a9a 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -13,11 +13,12 @@ def find_pytorch_dir(): OP_LIST = { - 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], - 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], - 'batch_norm_1d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], - 'batch_norm_2d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], - 'batch_norm_3d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], + # 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], + # 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], + 'batch_norm_1d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), ('aten::native_batch_norm_backward', 'aten::cudnn_batch_norm_backward')], + # 'batch_norm_1d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), 'aten::native_batch_norm_backward'], + # 'batch_norm_2d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], + # 'batch_norm_3d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], } @@ -39,14 +40,25 @@ def transform_to_us(time): if line.startswith('shape:'): flag = line for op in ops: - if op in line: - items = [] - for item in line.strip().split(' '): - if len(item) > 1: - items.append(item.strip()) - op_name = items[0] - op_time = transform_to_us(items[-2]) - res.append([op_name, flag, str(op_time)]) + if isinstance(op, tuple): + for op_ in op: + if op_ in line: + items = [] + for item in line.strip().split(' '): + if len(item) > 1: + items.append(item.strip()) + op_name = items[0] + op_time = transform_to_us(items[-2]) + res.append([op_name, flag, str(op_time)]) + else: + if op in line: + items = [] + for item in line.strip().split(' '): + if len(item) > 1: + items.append(item.strip()) + op_name = items[0] + op_time = transform_to_us(items[-2]) + res.append([op_name, flag, str(op_time)]) res_ = ["@@".join(item) for item in res] res_ = list(set(res_)) res = [item.split("@@") for item in res_] From 99d5592818604104f71683032067d7c3a304dd0a Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Wed, 14 May 2025 10:44:46 +0800 Subject: [PATCH 12/15] Update check_op_perf.py --- tools/check_op_perf.py | 24 +++++++++--------------- 1 file changed, 9 insertions(+), 15 deletions(-) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index c78482a9a..96d3abeae 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -35,30 +35,24 @@ def transform_to_us(time): else: raise Exception("time format not support") flag = "None" + print(text) for line in text.split('\n'): line = line.strip() if line.startswith('shape:'): flag = line for op in ops: - if isinstance(op, tuple): - for op_ in op: - if op_ in line: - items = [] - for item in line.strip().split(' '): - if len(item) > 1: - items.append(item.strip()) - op_name = items[0] - op_time = transform_to_us(items[-2]) - res.append([op_name, flag, str(op_time)]) - else: - if op in line: + if not isinstance(op, tuple): + op = (op,) + op_base_name = op[0] + for op_alias in op: + if op_alias in line: items = [] for item in line.strip().split(' '): if len(item) > 1: items.append(item.strip()) - op_name = items[0] - op_time = transform_to_us(items[-2]) - res.append([op_name, flag, str(op_time)]) + if items[0].strip() == op_alias: + op_time = transform_to_us(items[-2]) + res.append([op_base_name, flag, str(op_time)]) res_ = ["@@".join(item) for item in res] res_ = list(set(res_)) res = [item.split("@@") for item in res_] From d178db24f411b9996b4dae71fbffa62ae00ff94e Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Wed, 14 May 2025 10:59:34 +0800 Subject: [PATCH 13/15] Update check_op_perf.py --- tools/check_op_perf.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index 96d3abeae..ac9c7ad5c 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -15,7 +15,8 @@ def find_pytorch_dir(): OP_LIST = { # 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], # 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], - 'batch_norm_1d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), ('aten::native_batch_norm_backward', 'aten::cudnn_batch_norm_backward')], + 'batch_norm_1d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), + ('aten::native_batch_norm_backward', 'aten::cudnn_batch_norm_backward')], # 'batch_norm_1d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), 'aten::native_batch_norm_backward'], # 'batch_norm_2d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], # 'batch_norm_3d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], From f7dbe7c4346d8d10bbd9fd3ac460022b48217273 Mon Sep 17 00:00:00 2001 From: Yutao Xu Date: Wed, 14 May 2025 13:08:57 +0800 Subject: [PATCH 14/15] Update check_op_perf.py --- tools/check_op_perf.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/tools/check_op_perf.py b/tools/check_op_perf.py index ac9c7ad5c..61a03fbc9 100644 --- a/tools/check_op_perf.py +++ b/tools/check_op_perf.py @@ -13,12 +13,12 @@ def find_pytorch_dir(): OP_LIST = { - # 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], - # 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], + 'layer_norm.py': ['aten::native_layer_norm', 'aten::native_layer_norm_backward'], + 'group_norm.py': ['aten::native_group_norm', 'aten::native_group_norm_backward'], 'batch_norm_1d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), ('aten::native_batch_norm_backward', 'aten::cudnn_batch_norm_backward')], - # 'batch_norm_1d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), 'aten::native_batch_norm_backward'], - # 'batch_norm_2d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], + 'batch_norm_2d.py': [('aten::native_batch_norm', 'aten::cudnn_batch_norm'), + ('aten::native_batch_norm_backward', 'aten::cudnn_batch_norm_backward')], # 'batch_norm_3d.py': ['aten::native_batch_norm', 'aten::native_batch_norm_backward'], } From cb44f890b07f5c19134d437096d1b522a743bba1 Mon Sep 17 00:00:00 2001 From: Huaiyu Date: Tue, 20 May 2025 22:48:51 -0700 Subject: [PATCH 15/15] fix lint --- test/microbench/batch_norm_1d.py | 1 - test/microbench/batch_norm_2d.py | 1 - test/microbench/batch_norm_3d.py | 1 - test/microbench/group_norm.py | 1 - test/microbench/layer_norm.py | 1 - 5 files changed, 5 deletions(-) diff --git a/test/microbench/batch_norm_1d.py b/test/microbench/batch_norm_1d.py index 86aa5f386..1d837ccd2 100644 --- a/test/microbench/batch_norm_1d.py +++ b/test/microbench/batch_norm_1d.py @@ -1,7 +1,6 @@ import torch from torch.profiler import profile, ProfilerActivity - if torch.cuda.is_available(): device = "cuda" activity = ProfilerActivity.CUDA diff --git a/test/microbench/batch_norm_2d.py b/test/microbench/batch_norm_2d.py index 0abe5e5dc..aee88507c 100644 --- a/test/microbench/batch_norm_2d.py +++ b/test/microbench/batch_norm_2d.py @@ -1,7 +1,6 @@ import torch from torch.profiler import profile, ProfilerActivity - if torch.cuda.is_available(): device = "cuda" activity = ProfilerActivity.CUDA diff --git a/test/microbench/batch_norm_3d.py b/test/microbench/batch_norm_3d.py index bb94ba172..a7fbb0769 100644 --- a/test/microbench/batch_norm_3d.py +++ b/test/microbench/batch_norm_3d.py @@ -1,7 +1,6 @@ import torch from torch.profiler import profile, ProfilerActivity - if torch.cuda.is_available(): device = "cuda" activity = ProfilerActivity.CUDA diff --git a/test/microbench/group_norm.py b/test/microbench/group_norm.py index 252805bcd..f61795ac5 100644 --- a/test/microbench/group_norm.py +++ b/test/microbench/group_norm.py @@ -1,7 +1,6 @@ import torch from torch.profiler import profile, ProfilerActivity - if torch.cuda.is_available(): device = "cuda" activity = ProfilerActivity.CUDA diff --git a/test/microbench/layer_norm.py b/test/microbench/layer_norm.py index 639524129..c597a7cd1 100644 --- a/test/microbench/layer_norm.py +++ b/test/microbench/layer_norm.py @@ -1,7 +1,6 @@ import torch from torch.profiler import profile, ProfilerActivity - if torch.cuda.is_available(): device = "cuda" activity = ProfilerActivity.CUDA