From 33940965f7812decca45b5e23ebafcaaff243d10 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 12 Mar 2021 12:02:20 +0100
Subject: [PATCH 01/12] first CNN class try
---
mlair/model_modules/convolutional_networks.py | 113 ++++++++++++++++++
1 file changed, 113 insertions(+)
create mode 100644 mlair/model_modules/convolutional_networks.py
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
new file mode 100644
index 00000000..f9acdb72
--- /dev/null
+++ b/mlair/model_modules/convolutional_networks.py
@@ -0,0 +1,113 @@
+__author__ = "Lukas Leufen"
+__date__ = '2021-02-'
+
+from functools import reduce, partial
+
+from mlair.model_modules import AbstractModelClass
+from mlair.helpers import select_from_dict
+from mlair.model_modules.loss import var_loss, custom_loss
+from mlair.model_modules.advanced_paddings import PadUtils, Padding2D, SymmetricPadding2D
+
+import keras
+
+
+class CNN(AbstractModelClass):
+ _activation = {"relu": keras.layers.ReLU, "tanh": partial(keras.layers.Activation, "tanh"),
+ "sigmoid": partial(keras.layers.Activation, "sigmoid"),
+ "linear": partial(keras.layers.Activation, "linear"),
+ "selu": partial(keras.layers.Activation, "selu")}
+ _initializer = {"selu": keras.initializers.lecun_normal()}
+ _optimizer = {"adam": keras.optimizers.adam}
+ _regularizer = {"l1": keras.regularizers.l1, "l2": keras.regularizers.l2, "l1_l2": keras.regularizers.l1_l2}
+ _requirements = ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad"]
+
+ def __init__(self, input_shape: list, output_shape: list, activation="relu", activation_output="linear",
+ optimizer="adam", regularizer=None, **kwargs):
+
+ assert len(input_shape) == 1
+ assert len(output_shape) == 1
+ super().__init__(input_shape[0], output_shape[0])
+
+ # settings
+ self.activation = self._set_activation(activation)
+ self.activation_name = activation
+ self.activation_output = self._set_activation(activation_output)
+ self.activation_output_name = activation_output
+ self.kernel_initializer = self._initializer.get(activation, "glorot_uniform")
+ self.kernel_regularizer = self._set_regularizer(regularizer, **kwargs)
+ self.optimizer = self._set_optimizer(optimizer, **kwargs)
+
+ # apply to model
+ self.set_model()
+ self.set_compile_options()
+ self.set_custom_objects(loss=custom_loss([keras.losses.mean_squared_error, var_loss]), var_loss=var_loss)
+
+ def _set_activation(self, activation):
+ try:
+ return self._activation.get(activation.lower())
+ except KeyError:
+ raise AttributeError(f"Given activation {activation} is not supported in this model class.")
+
+ def _set_optimizer(self, optimizer, **kwargs):
+ try:
+ opt_name = optimizer.lower()
+ opt = self._optimizer.get(opt_name)
+ opt_kwargs = {}
+ if opt_name == "adam":
+ opt_kwargs = select_from_dict(kwargs, ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad"])
+ return opt(**opt_kwargs)
+ except KeyError:
+ raise AttributeError(f"Given optimizer {optimizer} is not supported in this model class.")
+
+ def _set_regularizer(self, regularizer, **kwargs):
+ if regularizer is None or (isinstance(regularizer, str) and regularizer.lower() == "none"):
+ return None
+ try:
+ reg_name = regularizer.lower()
+ reg = self._regularizer.get(reg_name)
+ reg_kwargs = {}
+ if reg_name in ["l1", "l2"]:
+ reg_kwargs = select_from_dict(kwargs, reg_name, remove_none=True)
+ if reg_name in reg_kwargs:
+ reg_kwargs["l"] = reg_kwargs.pop(reg_name)
+ elif reg_name == "l1_l2":
+ reg_kwargs = select_from_dict(kwargs, ["l1", "l2"], remove_none=True)
+ return reg(**reg_kwargs)
+ except KeyError:
+ raise AttributeError(f"Given regularizer {regularizer} is not supported in this model class.")
+
+ def set_model(self):
+ """
+ Build the model.
+ """
+ x_input = keras.layers.Input(shape=self._input_shape)
+ kernel = (1, 1)
+ pad_size = PadUtils.get_padding_for_same(kernel)
+ x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad")(x_input)
+ x_in = keras.layers.Conv2D(filters=16, kernel_size=kernel,
+ kernel_initializer=self.kernel_initializer,
+ kernel_regularizer=self.kernel_regularizer)(x_in)
+ x_in = self.activation()(x_in)
+ x_in = keras.layers.Conv2D(filters=32, kernel_size=kernel,
+ kernel_initializer=self.kernel_initializer,
+ kernel_regularizer=self.kernel_regularizer)(x_in)
+ x_in = self.activation()(x_in)
+ x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad")(x_in)
+ x_in = keras.layers.Conv2D(filters=64, kernel_size=kernel,
+ kernel_initializer=self.kernel_initializer,
+ kernel_regularizer=self.kernel_regularizer)(x_in)
+ x_in = self.activation()(x_in)
+ x_in = keras.layers.Flatten()(x_in)
+ x_in = keras.layers.Dense(64, kernel_initializer=self.kernel_initializer,
+ kernel_regularizer=self.kernel_regularizer)(x_in)
+ x_in = self.activation()(x_in)
+ x_in = keras.layers.Dense(16, kernel_initializer=self.kernel_initializer,
+ kernel_regularizer=self.kernel_regularizer)(x_in)
+ x_in = self.activation()(x_in)
+ x_in = keras.layers.Dense(self._output_shape)(x_in)
+ out = self.activation_output(name=f"{self.activation_output_name}_output")(x_in)
+ self.model = keras.Model(inputs=x_input, outputs=[out])
+
+ def set_compile_options(self):
+ self.compile_options = {"loss": [custom_loss([keras.losses.mean_squared_error, var_loss])],
+ "metrics": ["mse", "mae", var_loss]}
--
GitLab
From 30c27e99c0daf6ce0620745c23258c5da18450f8 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 12 Mar 2021 12:15:23 +0100
Subject: [PATCH 02/12] new pad layer names
---
mlair/model_modules/convolutional_networks.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index f9acdb72..e7d1da23 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -83,7 +83,7 @@ class CNN(AbstractModelClass):
x_input = keras.layers.Input(shape=self._input_shape)
kernel = (1, 1)
pad_size = PadUtils.get_padding_for_same(kernel)
- x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad")(x_input)
+ x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad1")(x_input)
x_in = keras.layers.Conv2D(filters=16, kernel_size=kernel,
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
@@ -92,7 +92,7 @@ class CNN(AbstractModelClass):
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
- x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad")(x_in)
+ x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad2")(x_in)
x_in = keras.layers.Conv2D(filters=64, kernel_size=kernel,
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
--
GitLab
From 7e529068a8f5c7c0010a2410e9e8389d667e4cd9 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 12 Mar 2021 12:43:19 +0100
Subject: [PATCH 03/12] bigger kernel
---
mlair/model_modules/convolutional_networks.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index e7d1da23..0a16be7c 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -81,7 +81,7 @@ class CNN(AbstractModelClass):
Build the model.
"""
x_input = keras.layers.Input(shape=self._input_shape)
- kernel = (1, 1)
+ kernel = (5, 1)
pad_size = PadUtils.get_padding_for_same(kernel)
x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad1")(x_input)
x_in = keras.layers.Conv2D(filters=16, kernel_size=kernel,
@@ -91,8 +91,8 @@ class CNN(AbstractModelClass):
x_in = keras.layers.Conv2D(filters=32, kernel_size=kernel,
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
+ x_in = keras.layers.MaxPooling2D(kernel, strides=(1, 1), padding='valid')(x_in)
x_in = self.activation()(x_in)
- x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad2")(x_in)
x_in = keras.layers.Conv2D(filters=64, kernel_size=kernel,
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
--
GitLab
From 7673e830a77c78f499c82909ca51d52e282a3609 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 12 Mar 2021 12:44:41 +0100
Subject: [PATCH 04/12] kernel size can be set from outside
---
mlair/model_modules/convolutional_networks.py | 5 +++--
1 file changed, 3 insertions(+), 2 deletions(-)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index 0a16be7c..5146fe52 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -22,7 +22,7 @@ class CNN(AbstractModelClass):
_requirements = ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad"]
def __init__(self, input_shape: list, output_shape: list, activation="relu", activation_output="linear",
- optimizer="adam", regularizer=None, **kwargs):
+ optimizer="adam", regularizer=None, kernel_size=1, **kwargs):
assert len(input_shape) == 1
assert len(output_shape) == 1
@@ -35,6 +35,7 @@ class CNN(AbstractModelClass):
self.activation_output_name = activation_output
self.kernel_initializer = self._initializer.get(activation, "glorot_uniform")
self.kernel_regularizer = self._set_regularizer(regularizer, **kwargs)
+ self.kernel_size = kernel_size
self.optimizer = self._set_optimizer(optimizer, **kwargs)
# apply to model
@@ -81,7 +82,7 @@ class CNN(AbstractModelClass):
Build the model.
"""
x_input = keras.layers.Input(shape=self._input_shape)
- kernel = (5, 1)
+ kernel = (self.kernel_size, 1)
pad_size = PadUtils.get_padding_for_same(kernel)
x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad1")(x_input)
x_in = keras.layers.Conv2D(filters=16, kernel_size=kernel,
--
GitLab
From 452b590c4b36008a70d1831da01874b9d4d90ac8 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 12 Mar 2021 14:47:18 +0100
Subject: [PATCH 05/12] no sympad for CNN
---
mlair/model_modules/convolutional_networks.py | 6 ++----
1 file changed, 2 insertions(+), 4 deletions(-)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index 5146fe52..2d8fd9e2 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -83,17 +83,15 @@ class CNN(AbstractModelClass):
"""
x_input = keras.layers.Input(shape=self._input_shape)
kernel = (self.kernel_size, 1)
- pad_size = PadUtils.get_padding_for_same(kernel)
- x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad1")(x_input)
x_in = keras.layers.Conv2D(filters=16, kernel_size=kernel,
kernel_initializer=self.kernel_initializer,
- kernel_regularizer=self.kernel_regularizer)(x_in)
+ kernel_regularizer=self.kernel_regularizer)(x_input)
x_in = self.activation()(x_in)
x_in = keras.layers.Conv2D(filters=32, kernel_size=kernel,
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
- x_in = keras.layers.MaxPooling2D(kernel, strides=(1, 1), padding='valid')(x_in)
x_in = self.activation()(x_in)
+ x_in = keras.layers.MaxPooling2D(kernel, strides=(1, 1), padding='valid')(x_in)
x_in = keras.layers.Conv2D(filters=64, kernel_size=kernel,
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
--
GitLab
From a9640da66f529382b584ea9c2dabf3ec420d7e34 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 12 Mar 2021 15:07:38 +0100
Subject: [PATCH 06/12] fix kernelsize for now
---
mlair/model_modules/convolutional_networks.py | 8 ++++----
1 file changed, 4 insertions(+), 4 deletions(-)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index 2d8fd9e2..329d1952 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -83,16 +83,16 @@ class CNN(AbstractModelClass):
"""
x_input = keras.layers.Input(shape=self._input_shape)
kernel = (self.kernel_size, 1)
- x_in = keras.layers.Conv2D(filters=16, kernel_size=kernel,
+ x_in = keras.layers.Conv2D(filters=16, kernel_size=(73, 1),
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_input)
x_in = self.activation()(x_in)
- x_in = keras.layers.Conv2D(filters=32, kernel_size=kernel,
+ x_in = keras.layers.Conv2D(filters=32, kernel_size=(49, 1),
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
- x_in = keras.layers.MaxPooling2D(kernel, strides=(1, 1), padding='valid')(x_in)
- x_in = keras.layers.Conv2D(filters=64, kernel_size=kernel,
+ x_in = keras.layers.MaxPooling2D((25, 1), strides=(1, 1), padding='valid')(x_in)
+ x_in = keras.layers.Conv2D(filters=64, kernel_size=(13, 1),
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
--
GitLab
From 56f3657c1c07eaa2b617ebf5b2d7435d7f97faa7 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 12 Mar 2021 15:24:49 +0100
Subject: [PATCH 07/12] changed dense layer
---
mlair/model_modules/convolutional_networks.py | 5 ++---
1 file changed, 2 insertions(+), 3 deletions(-)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index 329d1952..c4a10990 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -82,7 +82,6 @@ class CNN(AbstractModelClass):
Build the model.
"""
x_input = keras.layers.Input(shape=self._input_shape)
- kernel = (self.kernel_size, 1)
x_in = keras.layers.Conv2D(filters=16, kernel_size=(73, 1),
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_input)
@@ -97,10 +96,10 @@ class CNN(AbstractModelClass):
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
x_in = keras.layers.Flatten()(x_in)
- x_in = keras.layers.Dense(64, kernel_initializer=self.kernel_initializer,
+ x_in = keras.layers.Dense(128, kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
- x_in = keras.layers.Dense(16, kernel_initializer=self.kernel_initializer,
+ x_in = keras.layers.Dense(32, kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
x_in = keras.layers.Dense(self._output_shape)(x_in)
--
GitLab
From 01dc6fb2e6c26bbb03ee2c3d1827c77f24109743 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Fri, 26 Mar 2021 12:45:38 +0100
Subject: [PATCH 08/12] log more model information during model setup stage
---
HPC_setup/requirements_HDFML_additionals.txt | 1 +
HPC_setup/requirements_JUWELS_additionals.txt | 1 +
mlair/run_modules/model_setup.py | 26 ++++++++++++-------
requirements.txt | 1 +
requirements_gpu.txt | 1 +
5 files changed, 21 insertions(+), 9 deletions(-)
diff --git a/HPC_setup/requirements_HDFML_additionals.txt b/HPC_setup/requirements_HDFML_additionals.txt
index 12e09ccd..7d6163a6 100644
--- a/HPC_setup/requirements_HDFML_additionals.txt
+++ b/HPC_setup/requirements_HDFML_additionals.txt
@@ -9,6 +9,7 @@ chardet==4.0.0
coverage==5.4
cycler==0.10.0
dask==2021.2.0
+dill==0.3.3
fsspec==0.8.5
gast==0.4.0
grpcio==1.35.0
diff --git a/HPC_setup/requirements_JUWELS_additionals.txt b/HPC_setup/requirements_JUWELS_additionals.txt
index 12e09ccd..7d6163a6 100644
--- a/HPC_setup/requirements_JUWELS_additionals.txt
+++ b/HPC_setup/requirements_JUWELS_additionals.txt
@@ -9,6 +9,7 @@ chardet==4.0.0
coverage==5.4
cycler==0.10.0
dask==2021.2.0
+dill==0.3.3
fsspec==0.8.5
gast==0.4.0
grpcio==1.35.0
diff --git a/mlair/run_modules/model_setup.py b/mlair/run_modules/model_setup.py
index 5dd73d50..8fae430f 100644
--- a/mlair/run_modules/model_setup.py
+++ b/mlair/run_modules/model_setup.py
@@ -6,6 +6,7 @@ __date__ = '2019-12-02'
import logging
import os
import re
+from dill.source import getsource
import keras
import pandas as pd
@@ -57,12 +58,12 @@ class ModelSetup(RunEnvironment):
super().__init__()
self.model = None
exp_name = self.data_store.get("experiment_name")
- path = self.data_store.get("model_path")
+ self.path = self.data_store.get("model_path")
self.scope = "model"
- self.path = os.path.join(path, f"{exp_name}_%s")
- self.model_name = self.path % "%s.h5"
- self.checkpoint_name = self.path % "model-best.h5"
- self.callbacks_name = self.path % "model-best-callbacks-%s.pickle"
+ path = os.path.join(self.path, f"{exp_name}_%s")
+ self.model_name = path % "%s.h5"
+ self.checkpoint_name = path % "model-best.h5"
+ self.callbacks_name = path % "model-best-callbacks-%s.pickle"
self._train_model = self.data_store.get("train_model")
self._create_new_model = self.data_store.get("create_new_model")
self._run()
@@ -167,6 +168,7 @@ class ModelSetup(RunEnvironment):
keras.utils.plot_model(self.model, to_file=file_name, show_shapes=True, show_layer_names=True)
def report_model(self):
+ # report model settings
model_settings = self.model.get_settings()
model_settings.update(self.model.compile_options)
model_settings.update(self.model.optimizer.get_config())
@@ -179,17 +181,23 @@ class ModelSetup(RunEnvironment):
if "<" in str(v):
v = self._clean_name(str(v))
df.loc[k] = str(v)
+ df.loc["count params"] = str(self.model.count_params())
df.sort_index(inplace=True)
column_format = "ll"
path = os.path.join(self.data_store.get("experiment_path"), "latex_report")
path_config.check_path_and_create(path)
- df.to_latex(os.path.join(path, "model_settings.tex"), na_rep='---', column_format=column_format)
- df.to_markdown(open(os.path.join(path, "model_settings.md"), mode="w", encoding='utf-8'),
- tablefmt="github")
+ for p in [path, self.path]: # log to `latex_report` and `model`
+ df.to_latex(os.path.join(p, "model_settings.tex"), na_rep='---', column_format=column_format)
+ df.to_markdown(open(os.path.join(p, "model_settings.md"), mode="w", encoding='utf-8'), tablefmt="github")
+ # report model summary to file
+ with open(os.path.join(self.path, "model_summary.txt"), "w") as fh:
+ self.model.summary(print_fn=lambda x: fh.write(x + "\n"))
+ # print model code to file
+ with open(os.path.join(self.path, "model_code.txt"), "w") as fh:
+ fh.write(getsource(self.data_store.get("model_class")))
@staticmethod
def _clean_name(orig_name: str):
mod_name = re.sub(r'^{0}'.format(re.escape("<")), '', orig_name).replace("'", "").split(" ")
mod_name = mod_name[1] if any(map(lambda x: x in mod_name[0], ["class", "function", "method"])) else mod_name[0]
return mod_name[:-1] if mod_name[-1] == ">" else mod_name
-
diff --git a/requirements.txt b/requirements.txt
index b0a6e7f5..af742fde 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -9,6 +9,7 @@ chardet==4.0.0
coverage==5.4
cycler==0.10.0
dask==2021.2.0
+dill==0.3.3
fsspec==0.8.5
gast==0.4.0
grpcio==1.35.0
diff --git a/requirements_gpu.txt b/requirements_gpu.txt
index 35fe0d5e..7dd443a4 100644
--- a/requirements_gpu.txt
+++ b/requirements_gpu.txt
@@ -9,6 +9,7 @@ chardet==4.0.0
coverage==5.4
cycler==0.10.0
dask==2021.2.0
+dill==0.3.3
fsspec==0.8.5
gast==0.4.0
grpcio==1.35.0
--
GitLab
From ef3ced197933ea2e7c022b96f41254cbfbdd09e0 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Mon, 29 Mar 2021 12:08:51 +0200
Subject: [PATCH 09/12] added dropout to CNN
---
mlair/model_modules/convolutional_networks.py | 24 +++++++++++++++----
1 file changed, 19 insertions(+), 5 deletions(-)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index c4a10990..d4955d3d 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -12,17 +12,22 @@ import keras
class CNN(AbstractModelClass):
+
_activation = {"relu": keras.layers.ReLU, "tanh": partial(keras.layers.Activation, "tanh"),
"sigmoid": partial(keras.layers.Activation, "sigmoid"),
"linear": partial(keras.layers.Activation, "linear"),
- "selu": partial(keras.layers.Activation, "selu")}
- _initializer = {"selu": keras.initializers.lecun_normal()}
- _optimizer = {"adam": keras.optimizers.adam}
+ "selu": partial(keras.layers.Activation, "selu"),
+ "prelu": partial(keras.layers.PReLU, alpha_initializer=keras.initializers.constant(value=0.25))}
+ _initializer = {"tanh": "glorot_uniform", "sigmoid": "glorot_uniform", "linear": "glorot_uniform",
+ "relu": keras.initializers.he_normal(), "selu": keras.initializers.lecun_normal(),
+ "prelu": keras.initializers.he_normal()}
+ _optimizer = {"adam": keras.optimizers.adam, "sgd": keras.optimizers.SGD}
_regularizer = {"l1": keras.regularizers.l1, "l2": keras.regularizers.l2, "l1_l2": keras.regularizers.l1_l2}
- _requirements = ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad"]
+ _requirements = ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad", "momentum", "nesterov", "l1", "l2"]
+ _dropout = {"selu": keras.layers.AlphaDropout}
def __init__(self, input_shape: list, output_shape: list, activation="relu", activation_output="linear",
- optimizer="adam", regularizer=None, kernel_size=1, **kwargs):
+ optimizer="adam", regularizer=None, kernel_size=1, dropout=None, **kwargs):
assert len(input_shape) == 1
assert len(output_shape) == 1
@@ -37,6 +42,7 @@ class CNN(AbstractModelClass):
self.kernel_regularizer = self._set_regularizer(regularizer, **kwargs)
self.kernel_size = kernel_size
self.optimizer = self._set_optimizer(optimizer, **kwargs)
+ self.dropout, self.dropout_rate = self._set_dropout(activation, dropout)
# apply to model
self.set_model()
@@ -56,6 +62,8 @@ class CNN(AbstractModelClass):
opt_kwargs = {}
if opt_name == "adam":
opt_kwargs = select_from_dict(kwargs, ["lr", "beta_1", "beta_2", "epsilon", "decay", "amsgrad"])
+ elif opt_name == "sgd":
+ opt_kwargs = select_from_dict(kwargs, ["lr", "momentum", "decay", "nesterov"])
return opt(**opt_kwargs)
except KeyError:
raise AttributeError(f"Given optimizer {optimizer} is not supported in this model class.")
@@ -77,6 +85,12 @@ class CNN(AbstractModelClass):
except KeyError:
raise AttributeError(f"Given regularizer {regularizer} is not supported in this model class.")
+ def _set_dropout(self, activation, dropout_rate):
+ if dropout_rate is None:
+ return None, None
+ assert 0 <= dropout_rate < 1
+ return self._dropout.get(activation, keras.layers.Dropout), dropout_rate
+
def set_model(self):
"""
Build the model.
--
GitLab
From 1ea8b24f2b5af03d7d08a5c6f92738cd8f69135c Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Mon, 29 Mar 2021 12:28:15 +0200
Subject: [PATCH 10/12] join module now uses a retry strategy, /close #296 on
test success
---
mlair/helpers/join.py | 15 ++++++++++++++-
1 file changed, 14 insertions(+), 1 deletion(-)
diff --git a/mlair/helpers/join.py b/mlair/helpers/join.py
index 8a8ca0b8..e0b28660 100644
--- a/mlair/helpers/join.py
+++ b/mlair/helpers/join.py
@@ -8,6 +8,8 @@ from typing import Iterator, Union, List, Dict
import pandas as pd
import requests
+from requests.adapters import HTTPAdapter
+from requests.packages.urllib3.util.retry import Retry
from mlair import helpers
from mlair.configuration.join_settings import join_settings
@@ -129,13 +131,24 @@ def get_data(opts: Dict, headers: Dict) -> Union[Dict, List]:
:return: requested data (either as list or dictionary)
"""
url = create_url(**opts)
- response = requests.get(url, headers=headers)
+ response = retries_session().get(url, headers=headers)
if response.status_code == 200:
return response.json()
else:
raise EmptyQueryResult(f"There was an error (STATUS {response.status_code}) for request {url}")
+def retries_session(max_retries=5):
+ retry_strategy = Retry(total=max_retries,
+ status_forcelist=[429, 500, 502, 503, 504],
+ method_whitelist=["HEAD", "GET", "OPTIONS"])
+ adapter = HTTPAdapter(max_retries=retry_strategy)
+ http = requests.Session()
+ http.mount("https://", adapter)
+ http.mount("http://", adapter)
+ return http
+
+
def load_series_information(station_name: List[str], station_type: str_or_none, network_name: str_or_none,
join_url_base: str, headers: Dict, data_origin: Dict = None) -> [Dict, Dict]:
"""
--
GitLab
From 4dae57e381de56f823625f4b48269de6cdbe8f28 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Mon, 29 Mar 2021 14:31:08 +0200
Subject: [PATCH 11/12] use dropout in CNNs
---
mlair/model_modules/convolutional_networks.py | 4 ++++
1 file changed, 4 insertions(+)
diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index d4955d3d..624cfa09 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -104,11 +104,15 @@ class CNN(AbstractModelClass):
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
+ if self.dropout is not None:
+ x_in = self.dropout(self.dropout_rate)(x_in)
x_in = keras.layers.MaxPooling2D((25, 1), strides=(1, 1), padding='valid')(x_in)
x_in = keras.layers.Conv2D(filters=64, kernel_size=(13, 1),
kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
x_in = self.activation()(x_in)
+ if self.dropout is not None:
+ x_in = self.dropout(self.dropout_rate)(x_in)
x_in = keras.layers.Flatten()(x_in)
x_in = keras.layers.Dense(128, kernel_initializer=self.kernel_initializer,
kernel_regularizer=self.kernel_regularizer)(x_in)
--
GitLab
From 4a1d7679686026da0755dbdf6d2f492a57f13c52 Mon Sep 17 00:00:00 2001
From: leufen1 <l.leufen@fz-juelich.de>
Date: Mon, 29 Mar 2021 14:57:11 +0200
Subject: [PATCH 12/12] fix for #296 to reduce waiting if not internet
connection could be established
---
mlair/helpers/join.py | 5 +++--
1 file changed, 3 insertions(+), 2 deletions(-)
diff --git a/mlair/helpers/join.py b/mlair/helpers/join.py
index e0b28660..93cb0e7b 100644
--- a/mlair/helpers/join.py
+++ b/mlair/helpers/join.py
@@ -131,15 +131,16 @@ def get_data(opts: Dict, headers: Dict) -> Union[Dict, List]:
:return: requested data (either as list or dictionary)
"""
url = create_url(**opts)
- response = retries_session().get(url, headers=headers)
+ response = retries_session().get(url, headers=headers, timeout=(5, None)) # timeout=(open, read)
if response.status_code == 200:
return response.json()
else:
raise EmptyQueryResult(f"There was an error (STATUS {response.status_code}) for request {url}")
-def retries_session(max_retries=5):
+def retries_session(max_retries=3):
retry_strategy = Retry(total=max_retries,
+ backoff_factor=0.1,
status_forcelist=[429, 500, 502, 503, 504],
method_whitelist=["HEAD", "GET", "OPTIONS"])
adapter = HTTPAdapter(max_retries=retry_strategy)
--
GitLab