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(r0.12)Moon Yong Joon

1. 2. Data type3. Tensorflow 4. Tensor graph5. tensorboard

1.

anaconda windows7 anaconda pip tensorflow

Hello tensorflow python 3 (str) unicode str encoding bytes uncode type

Tensorflow /

Tensorflow

edges nodes graph

Tensorflow : (session)

tensorflow tf x 35 .y x + 5 global_variables_initializer 4 y

Tensorflow graph (session)

Tensorboard tensorboard

tensorboard graph graph

Tensorflow

Tensorflow Session fetch feed 2 FetcheFeeds fetch () Placeholder OPOPVAR

xfetchGraphfeed

With : Session with close()

fetch : Tensor Session tensoroperationTensor operation

fetch : Session.run Tensor

Tensorflow feed Session feed feed_dict

feed : Session.run Tensor

Assert

python assert assert

assert assert operation

assert assert operation

Numpy

numpy

(reduction_indices=1)

session

Tensorboard

tensorflow session summary tensorboard

tensorboard (localhost:6006)

Regression

Numpy :

n (y_data)(y)(^2),n.

Numpy : Operation

Tensorflow :

Tensorflow :

cost function

n (y_data)(y)(^2),n(Least-squares) .

Optimizer

class tf.train.Optimizertf.train.Optimizer class the API to add Ops to train a model, subclasses GradientDescentOptimizer, AdagradOptimizer, or MomentumOptimizer. tf.train.Optimizer GradientDescentOptimizer AdagradOptimizer MomentumOptimizer

class tf.train.GradientOptimizer (Gradient descent) train = optimizer.minimize(loss) (Gradient descent) (loss)

Gradient descent f(x ) , x0 . x i , x i+1 .

gamma i . f gamma i . , . x0 . .

tf.train.Optimizer.minimize compute_gradients () apply_gradients () , compute_gradients () apply_gradients ()

minimize

2. Data Type

Tensorclass

Tensorflow Session Tensor Class TensorSparseTensorTensorArray

Tensor class

Tensor 0 n 0 : 1 : 2 : 3 : 2 N : n-1

(rank)

dtype tensor data typePython typeDescriptionDT_FLOATtf.float3232 bits floating point.DT_DOUBLEtf.float6464 bits floating point.DT_INT8tf.int88 bits signed integer.DT_INT16tf.int1616 bits signed integer.DT_INT32tf.int3232 bits signed integer.DT_INT64tf.int6464 bits signed integer.DT_UINT8tf.uint88 bits unsigned integer.DT_STRINGtf.stringVariable length byte arrays. Each element of a Tensor is a byte array.DT_BOOLtf.boolBoolean.DT_COMPLEX64tf.complex64Complex number made of two 32 bits floating points: real and imaginary parts.DT_COMPLEX128tf.complex128Complex number made of two 64 bits floating points: real and imaginary parts.DT_QINT8tf.qint88 bits signed integer used in quantized Ops.DT_QINT32tf.qint3232 bits signed integer used in quantized Ops.DT_QUINT8tf.quint88 bits unsigned integer used in quantized Ops.

Variable:Tensor

tf.Variable() , , # Create a variable. y = tf.Variable(, name=)

tf.Variable() Tensor

: Tensor tf.Variable() y Variable

Numpy vs. Tensor numpy tensorflow array , ,

rank tensor rank

shape tensor shape

size tensor shape

: eval with Session

Variable : initialized_valueinitialized_value

Variable : assign assing, assign_add, assign_sub

global_variables global

variable_scopeVariable_scope

reuse_variables Variable_scope

get_variable Variable_scope

get_variable Variable_scope

reset_default_graph scope reset

:tensorboard

tensorboard

tensorboard

Placeholder:Tensor

placeholder placeholder tf.placeholder(dtype, shape=None, name=None)

Args: dtype: shape: tensor name: A name for the operation

Returns: ATensorthat may be used as a handle for feeding a value, but not evaluated directly.

placeholder Tensor placeholder Tensor

placeholder Tensor placeholder (feed)

Values : Tensor

constant tf.constant() a Tensor

zeros/zeros_like numpy tensorflow array

ones/ones_like 1 tensor

fill tensor value

Sequences : Tensor

linspace tensor .

range tensor .

Random : Tensor

random_normal 2 3 normal

random_normal : seed 2 3 normal

random_uniform 2 3 uniform

shuffle 3 2 shuffle

sparseTensorclass

SparseTensor

SparseTensor class. Tensor tensor session

TensorArrayclass

TensorArray

TensorArray , , Tensor . while_loop map_fn

TensorArray : write TensorArray write

TensorArray : read TensorArray read Tensor session

TensorArray : gather TensorArray gather Tensor session

pack/unpack

TensorArray TensorArray gather Tensor session

TensorArray : unpack/pack Tensor TensorArray

3. Tensorflow

Operation

Operation Operation

Operation Operation

Operation : graph Operation

Input & reader

placeholder feed_dict

placeholder_with_default feed_dict

File read

python open file

read_file Read_file

CSV: queue

csv file build csv_file

csv file csv decode

resize

transpose

: slice slice

Tensor

Tensor

: scalar scalar

, abs, neg, sign

neg negative

: / /

: cross a b . 3- 3 , , 3-

gradiants 2*x**2

complex:

Reduction/Scan

reduce_sum (reduction_indices=1)

reduce_mean/min/max

reduce_any/all True False

reduce_prod/logsumexp

accumulate_n shape

cumsum/cumprod

Segment

segment_sum/prod segment . Segment rank

segment_min/max segment min, max . Segment rank

transpose

diag

Matmul :

Inverse :

matrix_determinant :

trace

eye :

Tensorcontrol flow

tuple

identity

tuple tuple(list)

cond operation

case operation

while_loop 1 loop

while_loop 2 x loop

operation

Logical Operators operations

Comparison Operators operations

select tensor

where : x y None condition

where : x y

argmin/argmax /

unique/setdiff1d 2

Tensor

Scan

scan , .

scan :

scan : initializer : 1 initializer fn initializer . fn .

scan : initializer: 2 initializer fn initializer . fn .

Map/Fold

map_fn map . dtype

foldl / foldr , , fn

Tensor Transformations

Shaping

reshape numpy tensorflow array reshape

squeeze tensor size 1

expand_dims tensor axis

meshgrid ( 'xy') ( 'ij') , 'xy'()

Slicing and Joining

slice tensor slice tensor tf.slice(input_, begin, size, name=None)

reverse , dim bool

split tensor split axis

tile tensor tile

pad : constant tensor pad

pad : tensor pad

concat tensor tensor concat

pack/unpack numpy tensor

String

String/reduce join string_join/reduce_join

substr Tensor

encode/decode: base64 Tensor base64 /

string_split string_split SparseTensor values Tensor

histogram

histogram

histogram 3 2 shuffle

histogram_fixed_width histogram

4. Tensor graph

Building the graph( )

Tensorflow Graph session graph Building the graphLaunching the graph in a session

Graph

Tensorflow: graph graph nodes edges

Building the graphGraph tensor

tensor

Launching in a sessionSession run Tensor Operation

Product tensor tf.matmul(matrix1, matrix2)

Launching \the graph in a session()

Session

Session Session 2 Session.close() InteractiveSessionSessionInteractive . Tensor.eval(), Operation.run() Non-Interactive . Session.run()

Session

: Session , session

global_variables_initializer 1 operation Session.run .

global_variables_initializer 2 operation Session

Interactive Session

, InteraciveSession .initializer.run()

InteractiveSessionOperation.run(), Tensor.eval()

Interactive Usage Interactive tendor add

Interactive Usagesess = tf.InteractiveSession() ide

Interactive Usage 1Interactive tensor add

Session.run

Session Operation , Tensor operationtensorOperation.run() Tensor.eval()Session.run( _ )Session.run() operation tensor

Session.run : tensor

Session.run : operation runOperation: (attribute) .

Session.run fetches: graph grape , grape .feed_dict: graph options: A [RunOptions] protocol bufferrun_metadata: A [RunMetadata] protocol buffertf.Session.run(fetches, feed_dict=None, options=None, run_metadata=None)

Session : Session Session run with

sess = tf.InteractiveSession() tensor eval()

Session.run()Tensor.eval()

Session Session numpy.int32 Tensor

tensor

fetch

Session run () .

.

Feed

Placeholder sess feed_dict

rand_array feed_dict placeholder

Session feed Placeholder sess feed_dict

Session.run Session numpy.int32 Tensor

tensor

train.Savor

train.Savor

:

train.Savor

: train.Savor

Tensorflowgraph class

Moon Yong Joon

tf.Graph

graphGraph operation Tensor

OperationTensorrepresent units of computationrepresent the units of data that flow between operations.

graph as_default graph context Graph

tensorflow graph graph node

graph node ()Tf.get_default_graph() get_operations() op node

graph node ()

graph node () graph

graph node ()Op inputs

Tf.constant() tensor session

5. tensorboard

tensorboard

Tensorboard

Tensorboard localhost:6006

Summary

tf.summary.FileWriter summary

Graph localhost:6006

Graph : localhost:6006 GRAPHS

Graph session summary tensorboard

Graph : tensorboard (localhost:6006)

1 SummaryWriter summary.FileWriter , sess.graph_def sess.graph

2 ()

tensorboard

tensorboard : input input node tensorflow

Tensorflow : graph op namegraph = tf.get_default_graph() operation node

tensorboard : weight weight node

tensorboard : output output node tensorflow

Tensorboard

Tensorboard !tensorboard --logdir = C:\Users\06411\Documents\logs