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FastEstimator
fastestimator/fastestimator
Home
Install
Apphubs
Apphubs
Overview
Adversarial Training
Adversarial Training
Adversarial Robustness with Error Correcting Codes
Adversarial Robustness with Error Correcting Codes (and Hinge Loss)
Adversarial Training Using the Fast Gradient Sign Method (FGSM)
Anomaly Detection
Anomaly Detection
Anomaly Detection with Fastestimator
AutoML
AutoML
RandAug: automated data augmentation with reduced search space
Contrastive Learning
Contrastive Learning
SimCLR on CIFAIR10 Image Classification (Tensorflow Backend)
Curriculum Learning
Curriculum Learning
Curriculum Learning with SuperLoss (Tensorflow Backend)
Image Classification
Image Classification
CIFAR-10 Image Classification Using ResNet (PyTorch Backend)
Image Classification Using LeViT
MNIST Image Classification Using LeNet (Tensorflow Backend)
Image Classification with Deep Pyramidal Residual Networks
Image Classification Using Vision Transformer
Image Generation
Image Generation
Convolutional Variational Autoencoder using the MNIST dataset (TensorFlow backend)
Horse to Zebra Unpaired Image Translation with CycleGAN in FastEstimator
DCGAN on the MNIST Dataset
Progressive Growing GAN (PGGAN)
Instance Detection
Instance Detection
Instance Detection with RetinaNet
YOLOv5
Instance Segmentation
Instance Segmentation
SOLOv2
Keypoint Detection
Keypoint Detection
High-Resolution Net for Keypoint Detection
Learning Rate Scheduling
Learning Rate Scheduling
Super-Convergence Learning Rate Schedule (TensorFlow Backend)
Multi-task Learning
Multi-task Learning
Multi-Task Learning using Uncertainty Weighted Loss
Neural Architecture Search
Neural Architecture Search
Neural Architecture Search without Training (NASWOT) on CI10 (Tensorflow Backend)
Natural Language Processing (NLP)
Natural Language Processing (NLP)
Sentiment Prediction in IMDB Reviews using an LSTM
Languge Modeling using LSTM on Penn Treebank
Named Entity Recognition using BERT Fine-Tuning
Neural Machine Translation Using Transformer
One-shot Learning
One-shot Learning
One-Shot Learning using a Siamese Network in FastEstimator
Semantic Segmentation
Semantic Segmentation
Semantic segmentation using Line Search
Lung Segmentation Using the Montgomery Dataset
Microscopy Cell Segmentation Using Unet 3D 3plus
Image Style Transfer
Image Style Transfer
Fast Style Transfer with FastEstimator
Tabular Data
Tabular Data
Breast Cancer Detection
Tutorials
Tutorials
Beginner Tutorials
Beginner Tutorials
Tutorial 1: Getting Started
Tutorial 2: Creating a FastEstimator dataset
Tutorial 3: Operator
Tutorial 4: Pipeline
Tutorial 5: Model
Tutorial 6: Network
Tutorial 7: Estimator
Tutorial 8: Mode
Tutorial 9: Inference
Tutorial 10: How to use CLI
Tutorial 11: Debugging
Tutorial 12: Visualization
Advanced Tutorials
Advanced Tutorials
Advanced Tutorial 1: Dataset
Advanced Tutorial 2: Pipeline
Advanced Tutorial 3: Operator
Advanced Tutorial 4: Trace
Advanced Tutorial 5: Scheduler
Advanced Tutorial 6: Summary
Advanced Tutorial 7: Learning Rate Scheduling
Advanced Tutorial 8: Explainable AI (XAI)
Advanced Tutorial 9: Meta Ops
Advanced Tutorial 10: Automated Report Generation
Advanced Tutorial 11: Model Calibration
Advanced Tutorial 12: Hyperparameter Search
Advanced Tutorial 13: Multi-Dataset Training and Evaluation
Advanced Tutorial 14: Ops with Custom Data Loaders
Advanced Tutorial 15: Finetuning Tutorial
Advanced Tutorial 16: Model Robustness
Advanced Tutorial 17: Slicer
XAI Tutorials
XAI Tutorials
XAI Tutorial 1: Label Tracking
XAI Tutorial 2: Instance Tracking
XAI Tutorial 3: Saliency Maps
XAI Tutorial 4: EigenCAM
XAI Tutorial 5: GradCAM
API
API
fe
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estimator
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fe.architecture.pytorch
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resnet9
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wideresnet
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resnet9
unet
wideresnet
fe.backend
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_abs
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_binary_crossentropy
_cast
_categorical_crossentropy
_check_nan
_clip_by_value
_concat
_convert_tensor_precision
_dice_score
_exp
_expand_dims
_feed_forward
_flip
_focal_loss
_gather
_gather_from_batch
_get_gradient
_get_image_dims
_get_lr
_get_shape
_hinge
_huber
_iwd
_l1_loss
_l2_regularization
_lambertw
_load_model
_matmul
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_mean_squared_error
_ones_like
_percentile
_permute
_pow
_random_normal_like
_random_uniform_like
_reduce_max
_reduce_mean
_reduce_min
_reduce_std
_reduce_sum
_reshape
_resize3d
_roll
_save_model
_set_lr
_sign
_smooth_l1_loss
_sparse_categorical_crossentropy
_squeeze
_tensor_normalize
_tensor_pow
_tensor_round
_tensor_sqrt
_to_shape
_to_tensor
_to_type
_transpose
_update_model
_watch
_where
_zeros_like
_zscore
fe.cli
fe.cli
history
logs
main
plot
run
train
fe.dataset
fe.dataset
batch_dataset
combined_dataset
csv_dataset
fe.dataset.data
fe.dataset.data
breast_cancer
cifair10
cifair100
cifar10
cifar100
cub200
em_3d
food101
horse2zebra
imdb_review
medmnist
mendeley
mitmovie_ner
mnist
montgomery
mscoco
nih_chestxray
omniglot
pascal_voc
penn_treebank
shakespeare
skl_digits
svhn
svhn_cropped
tednmt
tiny_imagenet
usps
dataloader
dataset
dir_dataset
extend_dataset
generator_dataset
interleave_dataset
labeled_dir_dataset
numpy_dataset
op_dataset
pickle_dataset
siamese_dir_dataset
fe.layers
fe.layers
fe.layers.pytorch
fe.layers.pytorch
cropping_2d
hadamard
fe.layers.tensorflow
fe.layers.tensorflow
hadamard
instance_norm
reflection_padding_2d
fe.op
fe.op
fe.op.numpyop
fe.op.numpyop
fe.op.numpyop.meta
fe.op.numpyop.meta
fuse
one_of
repeat
sometimes
fe.op.numpyop.multivariate
fe.op.numpyop.multivariate
affine
center_crop
crop
crop_non_empty_mask_if_exists
elastic_transform
flip
grid_distortion
horizontal_flip
iaa_crop_and_pad
longest_max_size
mask_dropout
multivariate
optical_distortion
pad_if_needed
random_crop
random_crop_near_bbox
random_grid_shuffle
random_resized_crop
random_rotate_90
random_scale
random_sized_bbox_safe_crop
random_sized_crop
read_mat
resize
rotate
shift_scale_rotate
smallest_max_size
transpose
vertical_flip
numpyop
fe.op.numpyop.univariate
fe.op.numpyop.univariate
autocontrast
binarize
blur
brightness
calibate
channel_dropout
channel_shuffle
channel_transpose
clahe
coarse_dropout
color
color_jitter
contrast
downscale
equalize
expand_dims
from_float
gaussian_blur
gaussian_noise
hadamard
hue_saturation_value
iaa_additive_gaussian_noise
image_compression
invert_img
iso_noise
median_blur
minmax
motion_blur
multiplicative_noise
normalize
onehot
pad_sequence
posterize
random_brightness_contrast
random_fog
random_gamma
random_rain
random_shadow
random_shapes
random_snow
random_sun_flare
read_image
reshape
rgb_shift
rua
sharpness
shear_x
shear_y
solarize
tokenize
to_array
to_float
to_gray
to_sepia
translate_x
translate_y
univariate
word_to_id
op
fe.op.tensorop
fe.op.tensorop
argmax
fe.op.tensorop.augmentation
fe.op.tensorop.augmentation
cutmix_batch
mixup_batch
average
gather
fe.op.tensorop.gradient
fe.op.tensorop.gradient
fgsm
gradient
watch
fe.op.tensorop.loss
fe.op.tensorop.loss
cross_entropy
dice_loss
focal_loss
hinge
l1_loss
l2_regularization
loss
mean_squared_error
super_loss
fe.op.tensorop.meta
fe.op.tensorop.meta
fuse
one_of
repeat
sometimes
fe.op.tensorop.model
fe.op.tensorop.model
model
update
normalize
permute
reshape
resize3d
tensorop
un_hadamard
fe.schedule
fe.schedule
lr_schedule
schedule
fe.search
fe.search
golden_section
grid_search
search
fe.search.visualize
fe.search.visualize
cartesian
heatmap
parallel_coordinate_plot
visualize
vis_util
fe.slicer
fe.slicer
axis_slicer
mean_unslicer
slicer
sliding_slicer
fe.summary
fe.summary
history
fe.summary.logs
fe.summary.logs
log_parse
log_plot
summary
system
fe.test
fe.test
nightly_util
unittest_util
fe.trace
fe.trace
fe.trace.adapt
fe.trace.adapt
early_stopping
lr_scheduler
pbm_calibrator
reduce_lr_on_plateau
terminate_on_nan
fe.trace.io
fe.trace.io
batch_display
best_model_saver
csv_logger
grid_display
image_saver
image_viewer
model_saver
restore_wizard
tensorboard
test_report
traceability
fe.trace.meta
fe.trace.meta
_per_ds
fe.trace.metric
fe.trace.metric
accuracy
auc
bleu_score
calibration_error
confusion_matrix
dice
f1_score
mcc
mean_average_precision
precision
recall
trace
fe.trace.xai
fe.trace.xai
eigen_cam
grad_cam
instance_tracker
label_tracker
saliency
fe.util
fe.util
base_util
cli_util
data
google_download_util
img_data
latex_util
traceability_util
util
wget_util
fe.xai
fe.xai
saliency
vis_util
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