From 3d1dff560c10aaab07700ee7cb250dcafd775c1e Mon Sep 17 00:00:00 2001
From: Dennis Noll <dennis.noll@rwth-aachen.de>
Date: Tue, 28 Jul 2020 13:38:29 +0200
Subject: [PATCH] [keras] gfeed: removed validation
---
keras.py | 17 +++--------------
1 file changed, 3 insertions(+), 14 deletions(-)
diff --git a/keras.py b/keras.py
index 0598cd3..0f39c0e 100644
--- a/keras.py
+++ b/keras.py
@@ -93,7 +93,7 @@ class KFeed(object):
**kwargs,
)
- def gfeed(self, src, batch_size, rng=np.random, auto_steps=np.max, val_callbacks=[], **kwargs):
+ def gfeed(self, src, batch_size, rng=np.random, auto_steps=np.max, **kwargs):
"""
Creates a generator for tf.keras' model.fit().
Requires, that mean weights per process are equal:
@@ -105,7 +105,7 @@ class KFeed(object):
val[self.w] = self.balance_weights(val[self.w])
val = val.fuse(*val[self.w].keys())
val.blen
- ret = dict(
+ return dict(
dict(
zip(
("x", "steps_per_epoch"),
@@ -116,18 +116,6 @@ class KFeed(object):
workers=0,
**kwargs,
)
- for val_callback in val_callbacks:
- val_callback_copy = val_callback.copy()
- ret.setdefault("callbacks", []).insert(
- 0,
- val_callback_copy.pop("cls", CustomValidation)(
- **dict(
- zip(("x", "y", "sample_weight"), ret.get("validation_data")),
- **val_callback_copy,
- )
- ),
- )
- return ret
def gensteps(self, src, batch_size, rng=np.random, auto_steps=np.max):
keys = src.mkeys(self.all)
@@ -415,6 +403,7 @@ class PlotMulticlass(TFSummaryCallback):
self.truth = kwargs["y"]
self.sample_weight = kwargs.get("sample_weight", None)
self.class_names = class_names
+ self.plot_inputs = plot_inputs
self.columns = columns
self.to_file = to_file
--
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