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Global attention and other miscellaneous #3

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12 changes: 12 additions & 0 deletions conda_reqs.txt
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Original file line number Diff line number Diff line change
@@ -0,0 +1,12 @@
numpy
#torch
transformers
pyyaml
tqdm
loguru
ipython
torchsummary
pyjet
scipy
git+https://github.com/allenai/longformer.git
matplotlib
47 changes: 39 additions & 8 deletions grapple/data/torch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
import numpy as np
from tqdm import tqdm
from itertools import chain
import math


class PUDataset(IterableDataset):
Expand Down Expand Up @@ -69,10 +70,20 @@ def __iter__(self):
puppimet = data['puppimet']
pfmet = data['pfmet']

X = X[:, :self.n_particles, :]
Y = Y[:, :self.n_particles]
P = P[:, :self.n_particles]
Q = Q[:, :self.n_particles]
n_particles_raw = Y.shape[1]

if self.n_particles < n_particles_raw:
X = X[:, :self.n_particles, :]
Y = Y[:, :self.n_particles]
P = P[:, :self.n_particles]
Q = Q[:, :self.n_particles]
elif n_particles_raw < self.n_particles:
diff = self.n_particles - n_particles_raw
X = np.pad(X, (0, diff, 0))
Y = np.pad(Y, (0, diff))
P = np.pad(P, (0, diff))
Q = np.pad(Q, (0, diff))


mask_base = np.arange(X.shape[1])
idx = np.arange(X.shape[0])
Expand Down Expand Up @@ -276,14 +287,33 @@ def _get_len(self):
return n_tot

def __iter__(self):
np.random.shuffle(self._files)
for f in self._files[:self.num_max_files]:
files = self._files[:]
worker_info = torch.utils.data.get_worker_info()
if worker_info is not None:
per_worker = int(math.ceil(len(files) / worker_info.num_workers))
this_worker = worker_info.id
files = files[this_worker * per_worker : (this_worker+1) * per_worker]
np.random.shuffle(files)
for f in files[:self.num_max_files]:
raw_data = np.load(f)
data = raw_data['x']
met = raw_data['met']
jet1 = raw_data['jet1']

data = data[:, :self.n_particles, :]
if 'genz' in raw_data:
genz = raw_data['genz']
else:
genz = np.copy(met)

n_particles_raw = data.shape[1]
if n_particles_raw > self.n_particles:
data = data[:, :self.n_particles, :]
elif n_particles_raw < self.n_particles:
diff = self.n_particles - n_particles_raw
data = np.pad(
data,
pad_width=((0, 0), (0, diff), (0, 0)),
mode='constant', constant_values=0
)

X = data[:,:,[i for b,i in self.b2i.items() if b not in ('hardfrac', 'puppi')]]
y = data[:,:,self.b2i['hardfrac']]
Expand All @@ -303,6 +333,7 @@ def __iter__(self):
'mask': mask[i, :],
'neutral_mask': neutral_mask[i, :],
'genmet': met[i, :],
'genv': genz[i, :],
'jet1': jet1[i, :],
}

Expand Down
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