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Add test_fast_model_01().

master
Stanislaw Adaszewski 4 years ago
parent
commit
8edf8ce4f9
2 changed files with 57 additions and 2 deletions
  1. +7
    -2
      src/icosagon/fastmodel.py
  2. +50
    -0
      tests/icosagon/test_fastmodel.py

+ 7
- 2
src/icosagon/fastmodel.py View File

@@ -1,12 +1,16 @@
from .fastconv import FastConvLayer
from .bulkdec import BulkDecodeLayer
from .input import OneHotInputLayer
from .trainprep import PreparedData
import torch
import types
from typing import List, \
Union, \
Callable
class FastModel(torch.nn.Module):
def __init(self, prep_d: PreparedData,
def __init__(self, prep_d: PreparedData,
layer_dimensions: List[int] = [32, 64],
keep_prob: float = 1.,
rel_activation: Callable[[torch.Tensor], torch.Tensor] = lambda x: x,
@@ -20,6 +24,7 @@ class FastModel(torch.nn.Module):
layer_activation, dec_activation)
self.prep_d = prep_d
self.layer_dimensions = layer_dimensions
self.keep_prob = float(keep_prob)
self.rel_activation = rel_activation
self.layer_activation = layer_activation
@@ -55,7 +60,7 @@ class FastModel(torch.nn.Module):
def forward(self, _):
return self.seq(None)
def self._check_params(self, prep_d, layer_dimensions, rel_activation,
def _check_params(self, prep_d, layer_dimensions, rel_activation,
layer_activation, dec_activation):
if not isinstance(prep_d, PreparedData):


+ 50
- 0
tests/icosagon/test_fastmodel.py View File

@@ -0,0 +1,50 @@
from icosagon.fastmodel import FastModel
from icosagon.data import Data
from icosagon.trainprep import prepare_training, \
TrainValTest
import torch
import time
def _make_symmetric(x: torch.Tensor):
x = (x + x.transpose(0, 1)) / 2
return x
def _symmetric_random(n_rows, n_columns):
return _make_symmetric(torch.rand((n_rows, n_columns),
dtype=torch.float32).round().to_sparse())
def _some_data_with_interactions():
d = Data()
d.add_node_type('Gene', 1000)
d.add_node_type('Drug', 100)
fam = d.add_relation_family('Drug-Gene', 1, 0, True)
fam.add_relation_type('Target',
torch.rand((100, 1000), dtype=torch.float32).round().to_sparse())
fam = d.add_relation_family('Gene-Gene', 0, 0, True)
fam.add_relation_type('Interaction',
_symmetric_random(1000, 1000))
fam = d.add_relation_family('Drug-Drug', 1, 1, True)
for i in range(500):
fam.add_relation_type('Side Effect: Nausea %d' % i,
_symmetric_random(100, 100))
fam.add_relation_type('Side Effect: Infertility %d' % i,
_symmetric_random(100, 100))
fam.add_relation_type('Side Effect: Death %d' % i,
_symmetric_random(100, 100))
return d
def test_fast_model_01():
d = _some_data_with_interactions()
prep_d = prepare_training(d, TrainValTest(.8, .1, .1))
model = FastModel(prep_d)
for i in range(10):
t = time.time()
_ = model(None)
print('Model forward took:', time.time() - t)

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