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Fix temperature equation

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This commit is contained in:
James Betker 2020-07-14 10:17:14 -06:00
parent 853468ef82
commit 7659bd6818
2 changed files with 21 additions and 10 deletions
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7
codes/models/archs/SwitchedResidualGenerator_arch.py
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@ -294,9 +294,10 @@ class ConfigurableSwitchedResidualGenerator3(nn.Module):
def update_for_step(self, step, experiments_path='.'): def update_for_step(self, step, experiments_path='.'):
if self.attentions: if self.attentions:
temp = max(1, int( temp = max(1,
self.init_temperature * (self.final_temperature_step - step) / self.final_temperature_step)) 1 + self.init_temperature * (self.final_temperature_step - step) / self.final_temperature_step)
if temp == 1 and self.heightened_final_step and self.heightened_final_step != 1: if temp == 1 and self.heightened_final_step and step > self.final_temperature_step and \
self.heightened_final_step != 1:
# Once the temperature passes (1) it enters an inverted curve to match the linear curve from above. # Once the temperature passes (1) it enters an inverted curve to match the linear curve from above.
# without this, the attention specificity "spikes" incredibly fast in the last few iterations. # without this, the attention specificity "spikes" incredibly fast in the last few iterations.
h_steps_total = self.heightened_final_step - self.final_temperature_step h_steps_total = self.heightened_final_step - self.final_temperature_step

24
codes/utils/onnx_inference.py
View File

@ -2,11 +2,21 @@ import onnx
import numpy as np import numpy as np
import time import time
model = onnx.load('../results/gen.onnx') init_temperature = 10
final_temperature_step = 50
heightened_final_step = 90
heightened_temp_min = .1
outputs = {} for step in range(100):
for n in model.graph.node: temp = max(1, 1 + init_temperature * (final_temperature_step - step) / final_temperature_step)
for o in n.output: if temp == 1 and step > final_temperature_step and heightened_final_step and heightened_final_step != 1:
outputs[o] = n # Once the temperature passes (1) it enters an inverted curve to match the linear curve from above.
# without this, the attention specificity "spikes" incredibly fast in the last few iterations.
res = 0 h_steps_total = heightened_final_step - final_temperature_step
h_steps_current = min(step - final_temperature_step, h_steps_total)
# The "gap" will represent the steps that need to be traveled as a linear function.
h_gap = 1 / heightened_temp_min
temp = h_gap * h_steps_current / h_steps_total
# Invert temperature to represent reality on this side of the curve
temp = 1 / temp
print("%i: %f" % (step, temp))