import torch
from torch.autograd import grad
import pyro
from pyro import poutine
import inspect
import numpy as np
from showerSim.simulator import Simulator
from showerSim.utils import get_logger
import os
logger = get_logger()
class PyroSimulator(Simulator):
""" Pyro simulator interface """
def forward(self, inputs):
raise NotImplementedError
def trace(self, inputs):
# self.forward will be implemented when we create a simulator that inherits from PyroSimulator. And PyroSimulator inherits from Simulator where the __call__ method returns self.forwad (as in PyTorch)
return pyro.poutine.trace(self.forward).get_trace(inputs)
# -------------------------------
def augmented_data(self,
inputs,
inputs_num,
inputs_den,
exponential=True,
uniform=False):
"""
import numpy as np
import torch
import pprint
import matplotlib.pyplot as plt
import sys
import pickle
import argparse
import logging
import os
from showerSim import invMass_ginkgo
from showerSim.utils import get_logger
logger = get_logger(level=logging.WARNING)
augmented_data = False
# Nsamples=sys.argv[1]
# start = int(sys.argv[2])
# end = int(sys.argv[3])
#-----------------------
'''
Runs Ginkgo invariant mass toy parton shower
'''
parser = argparse.ArgumentParser(description="Generate synthetic jets")
parser.add_argument("-v",
"--verbose",
action="store_true",
help="Increase output verbosity")
parser.add_argument("--Nsamples",
import numpy as np
import torch
import pprint
import matplotlib.pyplot as plt
import sys
import pickle
import argparse
import logging
import os
from showerSim import exp2DShowerTree
from showerSim.utils import get_logger
logger = get_logger(level=logging.INFO)
augmented_data = False
# Nsamples=sys.argv[1]
# start = int(sys.argv[2])
# end = int(sys.argv[3])
#-----------------------
'''
Gaussian distribution shower
'''
parser = argparse.ArgumentParser(description="Generate synthetic jets")
parser.add_argument("-v",
"--verbose",
action="store_true",
help="Increase output verbosity")
parser.add_argument("--Nsamples",