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Refactor code to output result after each utterance infer (#7450)

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Dmitry Pigasin 2021-09-16 12:52:10 +03:00 committed by GitHub
parent cb80764f85
commit ffa07eb6f3
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1 changed files with 37 additions and 32 deletions
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69
inference-engine/ie_bridges/python/sample/speech_sample/speech_sample.py
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@ -228,10 +228,9 @@ def main():
# ---------------------------Step 7. Do inference---------------------------------------------------------------------- # ---------------------------Step 7. Do inference----------------------------------------------------------------------
log.info('Starting inference in synchronous mode') log.info('Starting inference in synchronous mode')
results = {blob_name: {} for blob_name in output_blobs} results = {blob_name: {} for blob_name in output_blobs}
infer_times = [] total_infer_time = 0
perf_counters = []
for key in sorted(input_data): for i, key in enumerate(sorted(input_data)):
start_infer_time = default_timer() start_infer_time = default_timer()
# Reset states between utterance inferences to remove a memory impact # Reset states between utterance inferences to remove a memory impact
@ -244,43 +243,49 @@ def main():
for blob_name in result.keys(): for blob_name in result.keys():
results[blob_name][key] = result[blob_name] results[blob_name][key] = result[blob_name]
infer_times.append(default_timer() - start_infer_time) infer_time = default_timer() - start_infer_time
perf_counters.append(exec_net.requests[0].get_perf_counts()) total_infer_time += infer_time
num_of_frames = file_data[0][key].shape[0]
avg_infer_time_per_frame = infer_time / num_of_frames
# ---------------------------Step 8. Process output-------------------------------------------------------------------- # ---------------------------Step 8. Process output--------------------------------------------------------------------
for blob_name in output_blobs: log.info('')
for i, key in enumerate(sorted(results[blob_name])): log.info(f'Utterance {i} ({key}):')
log.info(f'Utterance {i} ({key})') log.info(f'Total time in Infer (HW and SW): {infer_time * 1000:.2f}ms')
log.info(f'Frames in utterance: {num_of_frames}')
log.info(f'Average Infer time per frame: {avg_infer_time_per_frame * 1000:.2f}ms')
for blob_name in output_blobs:
log.info('')
log.info(f'Output blob name: {blob_name}') log.info(f'Output blob name: {blob_name}')
log.info(f'Frames in utterance: {results[blob_name][key].shape[0]}') log.info(f'Number scores per frame: {results[blob_name][key].shape[1]}')
log.info(f'Total time in Infer (HW and SW): {infer_times[i] * 1000:.2f}ms')
if args.reference: if args.reference:
log.info('')
compare_with_reference(results[blob_name][key], references[blob_name][key]) compare_with_reference(results[blob_name][key], references[blob_name][key])
if args.performance_counter: if args.performance_counter:
if 'GNA' in args.device: if 'GNA' in args.device:
pc = perf_counters[i] pc = exec_net.requests[0].get_perf_counts()
total_cycles = int(pc['1.1 Total scoring time in HW']['real_time']) total_cycles = int(pc['1.1 Total scoring time in HW']['real_time'])
stall_cycles = int(pc['1.2 Stall scoring time in HW']['real_time']) stall_cycles = int(pc['1.2 Stall scoring time in HW']['real_time'])
active_cycles = total_cycles - stall_cycles active_cycles = total_cycles - stall_cycles
frequency = 10**6 frequency = 10**6
if args.arch == 'CORE': if args.arch == 'CORE':
frequency *= GNA_CORE_FREQUENCY frequency *= GNA_CORE_FREQUENCY
else: else:
frequency *= GNA_ATOM_FREQUENCY frequency *= GNA_ATOM_FREQUENCY
total_inference_time = total_cycles / frequency total_inference_time = total_cycles / frequency
active_time = active_cycles / frequency active_time = active_cycles / frequency
stall_time = stall_cycles / frequency stall_time = stall_cycles / frequency
log.info('') log.info('')
log.info('Performance Statistics of GNA Hardware') log.info('Performance Statistics of GNA Hardware')
log.info(f' Total Inference Time: {(total_inference_time * 1000):.4f} ms') log.info(f' Total Inference Time: {(total_inference_time * 1000):.4f} ms')
log.info(f' Active Time: {(active_time * 1000):.4f} ms') log.info(f' Active Time: {(active_time * 1000):.4f} ms')
log.info(f' Stall Time: {(stall_time * 1000):.4f} ms') log.info(f' Stall Time: {(stall_time * 1000):.4f} ms')
log.info('') log.info('')
log.info(f'Total sample time: {total_infer_time * 1000:.2f}ms')
log.info(f'Total sample time: {sum(infer_times) * 1000:.2f}ms')
if args.output: if args.output:
for i, blob_name in enumerate(results): for i, blob_name in enumerate(results):