diff --git a/config.yml b/config.yml
index db94f2477a3ba9c04f9e44551398d661ee12d68d..31d1d30ef1b40ce6c9b4a6627919af2269346f7c 100644
--- a/config.yml
+++ b/config.yml
@@ -11,6 +11,12 @@ Dataset:
_ENCODING_INDEX: "I" # h(short) with 2 bytes should be sufficient
_ENCODING_OFFSET_FORMAT: ""
_ENCODING_ENDIAN: "<"
+ Transform: dataloader.composite_transform(dataloader.transform_remove_space_time(), dataloader.transform_normalize_with_train_statistics(MEAN, STD))
+ # Available transforms:
+ # dataloader.transform_remove_space_time()
+ # dataloader.transform_normalize_with_train_statistics(MEAN, STD)
+ # dataloader.transform_min_max_scaling(MIN, MAX)
+ # dataloader.composite_transform(dataloader.transform_remove_space_time(), dataloader.transform_min_max_scaling(MIN, MAX))
# Data Transformation
ApproximativeStats: True
@@ -31,6 +37,7 @@ ApproximativeMini: "torch.tensor([ 4.1479e+01, 6.0000e+00, 1.0182e+00, 1.2623
7.9218e+00, 1.0000e-11, 3.7171e+01, 2.5584e+00, 1.2075e+01,
-1.2436e+00, -9.9256e-01, -8.8131e-01])"
+
#Optimizer selection
Optimizer: Adam # in {Adam}
@@ -40,7 +47,7 @@ Training:
#Model selection
Model:
- Name: CNN1D
+ Name: BidirectionalLSTM
#choose in {LinearRegression, BidirectionalLSTM, RNN}
#Model parameters selection
@@ -51,9 +58,10 @@ LinearRegression:
Initialization: init_he
BidirectionalLSTM:
- HiddenSize: 16
- NumLayers: 1
- Dropout: 0.2
+ HiddenSize: 32
+ NumLayers: 4
+ LSTMDropout: 0
+ FFNDropout: 0.2
NumFFN: 8
Initialization: None
diff --git a/logs/main_unit_test.log b/logs/main_unit_test.log
index b1a1cf012abbfb66418dfe32cdd53ffdd8c03251..f9c0a53ef7ff80542a153d83a7eef4fb9be74ffd 100644
--- a/logs/main_unit_test.log
+++ b/logs/main_unit_test.log
@@ -2339,3 +2339,116 @@ INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and
INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
INFO:root: - The train fold has 541585 samples
INFO:root: - The valid fold has 135575 samples
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - Loaded a dataset with 677160 samples
+INFO:root: - Splitting the data in training and validation sets
+INFO:root:Generating the subset files from 677160 samples
+INFO:root: - Subset dataset
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - The train fold has 542010 samples
+INFO:root: - The valid fold has 135150 samples
+INFO:root:Building the dataloader
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 365 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2017-testing.nc.bin_index.idx
+INFO:root:I loaded 112860 values in the test set
+INFO:root:= Filling in the submission file
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - Loaded a dataset with 677160 samples
+INFO:root: - Splitting the data in training and validation sets
+INFO:root:Generating the subset files from 677160 samples
+INFO:root: - Subset dataset
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - The train fold has 541712 samples
+INFO:root: - The valid fold has 135448 samples
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - Loaded a dataset with 677160 samples
+INFO:root: - Splitting the data in training and validation sets
+INFO:root:Generating the subset files from 677160 samples
+INFO:root: - Subset dataset
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - The train fold has 541776 samples
+INFO:root: - The valid fold has 135384 samples
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - Loaded a dataset with 677160 samples
+INFO:root: - Splitting the data in training and validation sets
+INFO:root:Generating the subset files from 677160 samples
+INFO:root: - Subset dataset
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - The train fold has 541703 samples
+INFO:root: - The valid fold has 135457 samples
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - Loaded a dataset with 677160 samples
+INFO:root: - Splitting the data in training and validation sets
+INFO:root:Generating the subset files from 677160 samples
+INFO:root: - Subset dataset
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - The train fold has 541380 samples
+INFO:root: - The valid fold has 135780 samples
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - Loaded a dataset with 677160 samples
+INFO:root: - Splitting the data in training and validation sets
+INFO:root:Generating the subset files from 677160 samples
+INFO:root: - Subset dataset
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - The train fold has 542076 samples
+INFO:root: - The valid fold has 135084 samples
+INFO:root:= Dataloaders
+INFO:root: - Dataset creation
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Generating the index
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - Loaded a dataset with 677160 samples
+INFO:root: - Splitting the data in training and validation sets
+INFO:root:Generating the subset files from 677160 samples
+INFO:root: - Subset dataset
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root:The loaded dataset contains 25 latitudes, 37 longitudes, 28 depths and 2222 time points
+INFO:root:Loading the index from sub_2CMEMS-MEDSEA-2010-2016-training.nc.bin_index.idx
+INFO:root: - The train fold has 541214 samples
+INFO:root: - The valid fold has 135946 samples
diff --git a/main.py b/main.py
index e5edb4ad7abe53794cf3328b6ffe084b6f5afa23..07caa23043011ec203c9a082222b94a11d81d1d7 100644
--- a/main.py
+++ b/main.py
@@ -59,6 +59,8 @@ if __name__ == "__main__":
log_freq = int(cfg["Wandb"]["log_freq"])
log_interval = int(cfg["Wandb"]["log_interval"])
+ dataset_transform = cfg["Dataset"]["Transform"]
+
if not args.no_wandb:
wandb.init(entity = "wherephytoplankton", project = "Kaggle phytoplancton", config = {"batch_size": batch_size, "epochs": epochs})
@@ -93,8 +95,8 @@ if __name__ == "__main__":
valid_ratio,
overwrite_index = True,
max_num_samples=max_num_samples,
- train_transform=dataloader.composite_transform(dataloader.transform_remove_space_time(), dataloader.transform_min_max_scaling(MIN, MAX)),
- valid_transform=dataloader.composite_transform(dataloader.transform_remove_space_time(), dataloader.transform_min_max_scaling(MIN, MAX))
+ train_transform= eval(dataset_transfom),
+ valid_transform=eval(dataset_transfom)
)
if use_cuda :
@@ -133,4 +135,4 @@ if __name__ == "__main__":
utils.write_summary(logdir, network, optimizer, val_loss)
- create_submission.create_submission(network, dataloader.composite_transform(dataloader.transform_remove_space_time(), dataloader.transform_min_max_scaling(MIN, MAX)), device, rootDir, logdir)
+ create_submission.create_submission(network, eval(dataset_transfom), device, rootDir, logdir)
diff --git a/model.py b/model.py
index 58bb42c9b2a78e93619957a05a2f04d6e6f0485c..e0357c26028787515848e2d5fe8540c527da772a 100644
--- a/model.py
+++ b/model.py
@@ -76,10 +76,11 @@ class BidirectionalLSTM(nn.Module):
super(BidirectionalLSTM, self).__init__()
self.hidden_size = cfg["BidirectionalLSTM"]["HiddenSize"]
self.num_layers = cfg["BidirectionalLSTM"]["NumLayers"]
- self.dropout = cfg["BidirectionalLSTM"]["Dropout"]
+ self.LSTM_dropout = cfg["BidirectionalLSTM"]["LSTMDropout"]
+ self.FFN_dropout = cfg["DidirectionalLSTM"]["FFNDropout"]
self.num_ffn = cfg["BidirectionalLSTM"]["NumFFN"]
- self.lstm = nn.LSTM(input_size, self.hidden_size, self.num_layers, batch_first = True, bidirectional =True, dropout = 0.2)
+ self.lstm = nn.LSTM(input_size, self.hidden_size, self.num_layers, batch_first = True, bidirectional =True, dropout = self.LSTM_dropout)
self.fc = nn.Sequential()
for layer in range(self.num_ffn):
@@ -92,7 +93,7 @@ class BidirectionalLSTM(nn.Module):
)
self.fc.add_module(
f"dropout_{layer}",
- nn.Dropout(p=self.dropout)
+ nn.Dropout(p=self.FFN_dropout)
)
self.fc.add_module(
"last_linear",
@@ -120,16 +121,15 @@ class CNN1D(torch.nn.Module):
def __init__(self, cfg, num_inputs):
super(CNN1D, self).__init__()
self.model = torch.nn.Sequential(
- *conv_block(num_inputs, 6, 0.01),
- *conv_block(64, 7, 0.01),
- *conv_block(128,8,0.01)
+ *conv_block(num_inputs, 32),
+ *conv_block(32, 128)
)
self.avg_pool = torch.nn.AdaptiveAvgPool1d(1)
- self.fc = nn.Sequential(
- nn.Linear(256, 32),
+ self.ffn = nn.Sequential(
+ nn.Linear(128, 128),
nn.ReLU(),
- nn.Linear(32,cfg["Dataset"]["num_days"])
+ nn.Linear(128,cfg["Dataset"]["num_days"])
)
def forward(self, x):
@@ -137,25 +137,21 @@ class CNN1D(torch.nn.Module):
out = self.model(x)
+ print(f"This is after CNN : {out}")
out = self.avg_pool(out)
out = out.view([out.shape[0], -1])
- out = self.fc(out)
+ #print(f"{out.shape} this is out.shape")
+ out = self.ffn(out)
out = out.view([out.shape[0], out.shape[1], 1])
return out
-def conv_block(in_channels, power, dropout_p):
+def conv_block(in_channels, out_channels):
return [
- torch.nn.Conv1d(in_channels, 2**power, 16),
- #torch.nn.BatchNorm1d(2**power),
- torch.nn.LeakyReLU(),
- torch.nn.Dropout(p=dropout_p),
- torch.nn.Conv1d(2**power, 2**power, 8),
- torch.nn.BatchNorm1d(2**power),
- torch.nn.LeakyReLU(),
- #torch.nn.Dropout(p=dropout_p),
- torch.nn.MaxPool1d(2, stride = 1)
+ torch.nn.Conv1d(in_channels, out_channels, kernel_size = 3, stride = 1, padding = 1),
+ torch.nn.ReLU(),
+ torch.nn.BatchNorm1d(out_channels),
]
# Initialization
diff --git a/train_indices.subset b/train_indices.subset
index 82ff06c8175de13333850a1293f875a45886aa20..4be28c3fddee04d316099595035195d190335a28 100644
Binary files a/train_indices.subset and b/train_indices.subset differ
diff --git a/valid_indices.subset b/valid_indices.subset
index 2879dd700471194d299571d05e917450856b3b49..71e2f411ff24dec16c1ec6873ea24d6a85512515 100644
Binary files a/valid_indices.subset and b/valid_indices.subset differ
diff --git a/wandb/debug-internal.log b/wandb/debug-internal.log
index 3245817b8c808dd5a25d2e3f8f4b128923c4a702..86e3c6db85a338ab8d678250d88aa44012db1885 120000
--- a/wandb/debug-internal.log
+++ b/wandb/debug-internal.log
@@ -1 +1 @@
-run-20230204_013952-5w9xw0aw/logs/debug-internal.log
\ No newline at end of file
+run-20230204_131220-udsbqzli/logs/debug-internal.log
\ No newline at end of file
diff --git a/wandb/debug.log b/wandb/debug.log
index ed90b7c5344b414587e2d31a200dbf31684c1568..f159925d26b61b22c8fb7b0fc268b4daba398c32 120000
--- a/wandb/debug.log
+++ b/wandb/debug.log
@@ -1 +1 @@
-run-20230204_013952-5w9xw0aw/logs/debug.log
\ No newline at end of file
+run-20230204_131220-udsbqzli/logs/debug.log
\ No newline at end of file
diff --git a/wandb/latest-run b/wandb/latest-run
index 9fa788a3b33b1984e1c4241a02fb397cf5ef142f..c44486eefedb3139505e9e4dd55a4a1c8354a55b 120000
--- a/wandb/latest-run
+++ b/wandb/latest-run
@@ -1 +1 @@
-run-20230204_013952-5w9xw0aw
\ No newline at end of file
+run-20230204_131220-udsbqzli
\ No newline at end of file