69 lines
2.8 KiB
Python
69 lines
2.8 KiB
Python
import json
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import os
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class BaseAgent(object):
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''' Base class for an REVERIE agent to generate and save trajectories. '''
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def __init__(self, env):
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self.env = env
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self.results = {}
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def get_results(self, detailed_output=False):
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output = []
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for k, v in self.results.items():
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output.append({'instr_id': k, 'trajectory': v['path']})
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if detailed_output:
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output[-1]['details'] = v['details']
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output[-1]['action_plan'] = v['action_plan']
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output[-1]['llm_output'] = v['llm_output']
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output[-1]['llm_thought'] = v['llm_thought']
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output[-1]['llm_observation'] = v['llm_observation']
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output[-1]['final_state'] = v['final_state']
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return output
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def rollout(self, **args):
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''' Return a list of dicts containing instr_id:'xx', path:[(viewpointId, heading_rad, elevation_rad)] '''
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raise NotImplementedError
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@staticmethod
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def get_agent(name):
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return globals()[name+"Agent"]
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def test(self, iters=None, **kwargs):
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# self.env.reset_epoch(shuffle=(iters is not None)) # If iters is not none, shuffle the env batch
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self.losses = []
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self.results = {}
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# We rely on env showing the entire batch before repeating anything
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looped = False
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self.loss = 0
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if iters is not None:
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# For each time, it will run the first 'iters' iterations. (It was shuffled before)
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for i in range(iters):
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for traj in self.rollout(**kwargs):
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self.loss = 0
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self.results[traj['instr_id']] = traj
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preds_detail = self.get_results(detailed_output=True)
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json.dump(
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preds_detail,
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open(os.path.join(self.config.log_dir, 'runtime.json'), 'w'),
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sort_keys=True, indent=4, separators=(',', ': ')
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)
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else: # Do a full round
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while True:
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for traj in self.rollout(**kwargs):
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print(f"ID: {traj['instr_id']}")
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print(self.results.keys())
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if traj['instr_id'] in self.results:
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looped = True
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else:
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self.loss = 0
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self.results[traj['instr_id']] = traj
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preds_detail = self.get_results(detailed_output=True)
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json.dump(
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preds_detail,
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open(os.path.join(self.config.log_dir, 'runtime.json'), 'w'),
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sort_keys=True, indent=4, separators=(',', ': ')
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)
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if looped:
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break
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