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Update num_processes config for FARMReader

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This commit is contained in:
Tanay Soni 2020-04-20 16:09:23 +02:00
parent 07df974880
commit f8da804a91
1 changed files with 2 additions and 3 deletions
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haystack/reader/farm.py
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@ -83,7 +83,7 @@ class FARMReader:
self.top_k_per_candidate = top_k_per_candidate self.top_k_per_candidate = top_k_per_candidate
self.inferencer = Inferencer.load(model_name_or_path, batch_size=batch_size, gpu=use_gpu, self.inferencer = Inferencer.load(model_name_or_path, batch_size=batch_size, gpu=use_gpu,
task_type="question_answering", max_seq_len=max_seq_len, task_type="question_answering", max_seq_len=max_seq_len,
doc_stride=doc_stride) doc_stride=doc_stride, num_processes=num_processes)
self.inferencer.model.prediction_heads[0].context_window_size = context_window_size self.inferencer.model.prediction_heads[0].context_window_size = context_window_size
self.inferencer.model.prediction_heads[0].no_ans_boost = no_ans_boost self.inferencer.model.prediction_heads[0].no_ans_boost = no_ans_boost
self.inferencer.model.prediction_heads[0].n_best = top_k_per_candidate + 1 # including possible no_answer self.inferencer.model.prediction_heads[0].n_best = top_k_per_candidate + 1 # including possible no_answer
@ -91,7 +91,6 @@ class FARMReader:
self.inferencer.model.prediction_heads[0].n_best_per_sample = top_k_per_sample self.inferencer.model.prediction_heads[0].n_best_per_sample = top_k_per_sample
except: except:
logger.warning("Could not set `top_k_per_sample` in FARM. Please update FARM version.") logger.warning("Could not set `top_k_per_sample` in FARM. Please update FARM version.")
self.num_processes = num_processes
self.max_seq_len = max_seq_len self.max_seq_len = max_seq_len
self.use_gpu = use_gpu self.use_gpu = use_gpu
@ -227,7 +226,7 @@ class FARMReader:
# get answers from QA model # get answers from QA model
predictions = self.inferencer.inference_from_dicts( predictions = self.inferencer.inference_from_dicts(
dicts=input_dicts, rest_api_schema=True, num_processes=self.num_processes, multiprocessing_chunksize=1 dicts=input_dicts, rest_api_schema=True, multiprocessing_chunksize=1
) )
# assemble answers from all the different documents & format them. # assemble answers from all the different documents & format them.
# For the "no answer" option, we collect all no_ans_gaps and decide how likely # For the "no answer" option, we collect all no_ans_gaps and decide how likely