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replacing the deprecated input-file of qaic-runner with json-input #15

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replacing the deprecated input-file of qaic-runner with json-input #15

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16 changes: 12 additions & 4 deletions models/language_processing/encoder/run_nlp_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,27 +86,33 @@ def generate_random_data(model_path, BS, SL, INPUT_FOLDER):
return
data_files = []
ort_inputs = {}
aic_batch_io = {"IO-files": [[]]}
if len(model.graph.input) >= 1:
input_ids = torch.randint(0, vocab_size, (BS, SL))
input_ids_file = f"{INPUT_FOLDER}input_ids_{BS}x{SL}.raw"
input_ids.numpy().astype(np.int64).tofile(input_ids_file)
data_files.append(input_ids_file)
ort_inputs['input_ids']=input_ids.numpy().astype(np.int64)
aic_batch_io["IO-files"][0].append({"path":f"input_ids_{BS}x{SL}.raw", "io-direction": "in", "elem-size": 8, "map-to": "input_ids", "dims": [BS, SL]})
if len(model.graph.input) >= 2:
attention_mask = torch.ones((BS, SL))
attention_mask_file = f"{INPUT_FOLDER}attention_mask_{BS}x{SL}.raw"
attention_mask.numpy().astype(np.int64).tofile(attention_mask_file)
data_files.append(attention_mask_file)
ort_inputs['attention_mask']=attention_mask.numpy().astype(np.int64)
aic_batch_io["IO-files"][0].append({"path":f"attention_mask_{BS}x{SL}.raw", "io-direction": "in", "elem-size": 8, "map-to": "attention_mask", "dims": [BS, SL]})
if len(model.graph.input) >= 3:
token_type_ids = torch.ones((BS, SL))
token_type_ids_file = f"{INPUT_FOLDER}token_type_ids_{BS}x{SL}.raw"
token_type_ids.numpy().astype(np.int64).tofile(token_type_ids_file)
data_files.append(token_type_ids_file)
ort_inputs['token_type_ids']=token_type_ids.numpy().astype(np.int64)
aic_batch_io["IO-files"][0].append({"path":f"token_type_ids_{BS}x{SL}.raw", "io-direction": "in", "elem-size": 8, "map-to": "token_type_ids", "dims": [BS, SL]})
input_list_file = f'./list_{BS}x{SL}.txt'
with open(input_list_file, 'w') as fid:
fid.write(','.join(data_files))
with open(f"{INPUT_FOLDER}aic_batch_io.json", "w") as f:
json.dump(aic_batch_io, f, indent=1)
print(f"The random input samples are saved at {INPUT_FOLDER} and are addressed by {input_list_file}", flush=True)
return ort_inputs, data_files, input_list_file

Expand Down Expand Up @@ -413,10 +419,12 @@ def infer(input_data):
"--aic-profiling-out-dir", run_output_dir,
"-write-output-dir", run_output_dir,
"-S", f"{SET_SIZE}",
"-d", f"{DEVICE_ID}"
"-d", f"{DEVICE_ID}",
"--aic-batch-json-input", "./inputFiles/aic_batch_io.json"
]
for data_file in data_files:
cmd_elements.extend(["-i", data_file])

# for data_file in data_files:
# cmd_elements.extend(["-i", data_file])
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Why leave dead code in? You could just as easily remove it

execute(cmd_elements, f"commands-{MOTIF}.txt", 'a')

latency_method = '95pct'
Expand Down Expand Up @@ -538,4 +546,4 @@ def parse_args():

if __name__ == "__main__":
args = parse_args()
main(args)
main(args)
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What did you do here? The diff looks like no change

14 changes: 10 additions & 4 deletions models/vision/classification/run_cv_classifier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
from glob import glob
import time
import threading
import json

import torchvision
from transformers import ResNetForImageClassification, ViTForImageClassification
Expand Down Expand Up @@ -113,6 +114,7 @@ def generate_random_data(model_path, BS, IS, INPUT_FOLDER):
return

ort_inputs = {}
aic_batch_io = {"IO-files": [[]]}
os.makedirs(INPUT_FOLDER, exist_ok=True)
dummy_input = torch.randn(BS, 3, IS, IS)
image_file = f"{INPUT_FOLDER}input_img_{BS}x3x{IS}x{IS}.raw"
Expand All @@ -123,6 +125,9 @@ def generate_random_data(model_path, BS, IS, INPUT_FOLDER):
file.write(','.join(data_files))
print(f"The random input samples are saved at {INPUT_FOLDER} and are addressed by {input_list_file}", flush=True)
input_name = model.graph.input[0].name
aic_batch_io["IO-files"][0].append({"path":f"input_img_{BS}x3x{IS}x{IS}.raw", "io-direction": "in", "elem-size": 4, "map-to": input_name, "dims": [BS, 3, IS, IS]})
with open(f"{INPUT_FOLDER}aic_batch_io.json", "w") as f:
json.dump(aic_batch_io, f, indent=1)
ort_inputs[input_name]=dummy_input.numpy().astype(np.float32)
return ort_inputs, data_files, input_list_file

Expand Down Expand Up @@ -346,10 +351,11 @@ def main(args):
"--aic-profiling-out-dir", run_output_dir,
"-write-output-dir", run_output_dir,
"-S", f"{SET_SIZE}",
"-d", f"{DEVICE_ID}"
"-d", f"{DEVICE_ID}",
"--aic-batch-json-input", "./inputFiles/aic_batch_io.json"
]
for data_file in data_files:
cmd_elements.extend(["-i", data_file])
# for data_file in data_files:
# cmd_elements.extend(["-i", data_file])
execute(cmd_elements, f"commands-{MOTIF}.txt", 'a')

# # computes the device avg power during runtime
Expand Down Expand Up @@ -489,4 +495,4 @@ def parse_args():

if __name__ == "__main__":
args = parse_args()
main(args)
main(args)
14 changes: 10 additions & 4 deletions models/vision/detection/run_yolo_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@
import torchvision
import pandas as pd
from glob import glob
import json

# computes the average or percentile for a pandas.Series object
def get_metric(series, method):
Expand Down Expand Up @@ -144,6 +145,7 @@ def generate_random_data(model_path, BS, IS, INPUT_FOLDER):
return

ort_inputs = {}
aic_batch_io = {"IO-files": [[]]}
os.makedirs(INPUT_FOLDER, exist_ok=True)
dummy_input = torch.randn(BS, 3, IS, IS)
image_file = f"{INPUT_FOLDER}input_img_{BS}x3x{IS}x{IS}.raw"
Expand All @@ -154,6 +156,9 @@ def generate_random_data(model_path, BS, IS, INPUT_FOLDER):
file.write(','.join(data_files))
print(f"The random input samples are saved at {INPUT_FOLDER} and are addressed by {input_list_file}", flush=True)
input_name = model.graph.input[0].name
aic_batch_io["IO-files"][0].append({"path":f"input_img_{BS}x3x{IS}x{IS}.raw", "io-direction": "in", "elem-size": 4, "map-to": input_name, "dims": [BS, 3, IS, IS]})
with open(f"{INPUT_FOLDER}aic_batch_io.json", "w") as f:
json.dump(aic_batch_io, f, indent=1)
ort_inputs[input_name]=dummy_input.numpy().astype(np.float32)
return ort_inputs, data_files, input_list_file

Expand Down Expand Up @@ -384,10 +389,11 @@ def main(args):
"--aic-profiling-out-dir", run_output_dir,
"-write-output-dir", run_output_dir,
"-S", f"{SET_SIZE}",
"-d", f"{DEVICE_ID}"
"-d", f"{DEVICE_ID}",
"--aic-batch-json-input", "./inputFiles/aic_batch_io.json"
]
for data_file in data_files:
cmd_elements.extend(["-i", data_file])
# for data_file in data_files:
# cmd_elements.extend(["-i", data_file])
execute(cmd_elements, f"commands-{MOTIF}.txt", 'a')

latency_method = '95pct'
Expand Down Expand Up @@ -508,4 +514,4 @@ def parse_args():

if __name__ == "__main__":
args = parse_args()
main(args)
main(args)