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Scalac hanging in phase typer


Scalac hanging in phase typer

By : Sasquatchahatchie
Date : November 18 2020, 01:01 AM
will be helpful for those in need Thank you Cvogt, upgrading to 2.11 did the trick. As you said, this is a problem with the 2.10.3 compiler and seems to be fixed now.
code :


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What are <stable> and <accessor> when doing Scalac -Xprint:typer?

What are <stable> and <accessor> when doing Scalac -Xprint:typer?


By : Cristiano Veiga
Date : March 29 2020, 07:55 AM
will help you These are internal (i.e., not exposed through the new 2.10 reflection API) flags. The official compiler ScalaDoc site seems to be down, but you can see the Scala source for details:
code :
final val STABLE   = 1 << 22 // functions that are assumed to be stable
                             // (typically, access methods for valdefs)
                             // or classes that do not contain abstract types.
final val ACCESSOR = 1 << 27 // a value or variable accessor (getter or setter)
How turn off/on typer phase in scala repl and sbt console

How turn off/on typer phase in scala repl and sbt console


By : Sofiya
Date : March 29 2020, 07:55 AM
With these it helps Is it possible to switch phase without exiting from current session? I've tried entering :power mode, but it still doesn't print types. , In SBT just add the following setting:
code :
set scalacOptions in (Compile, console) := "-Xprint:typer"
The Little Typer

The Little Typer


By : leftblank
Date : March 29 2020, 07:55 AM
like below fixes the issue First you need to install pie. In DrRacket you can do this with: File > Package Manager... > Do What I Mean, typing pie in the package source field, and clicking Install.
Alternatively, if you're using the command line you can install it with the command:
code :
raco pkg install pie
#lang pie

(claim two-plus-two-is-four
  (= Nat (+ 2 2) 4))
tensorflow keras can't keep dropout during prediction phase (set learning phase not working)

tensorflow keras can't keep dropout during prediction phase (set learning phase not working)


By : user3316848
Date : March 29 2020, 07:55 AM
I wish did fix the issue. The Dropout layer takes a training parameter that controls whether or not it is in training mode. Looking at the code on github, in the absence of the training parameter it should use the learning phase that has been set explicitly.
However, maybe this behaviour has changed somehow. This github thread suggests setting the training parameter explicitly, for example, as one commenter wrote:
code :
import tensorflow.keras

inputs = tensorflow.keras.Input(shape=(10,))
x = tensorflow.keras.layers.Dense(3)(inputs)
outputs = tensorflow.keras.layers.Dropout(0.5)(x, training=True)

model = tensorflow.keras.Model(inputs, outputs)
Three phases of recovery : the analysis phase, the redo phase, and finally the undo phase

Three phases of recovery : the analysis phase, the redo phase, and finally the undo phase


By : user3852212
Date : October 15 2020, 01:19 AM
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