## 0.51.0

* Re-export utils from Starlette:
    * This allows using things like `from fastapi.responses import JSONResponse` instead of `from starlette.responses import JSONResponse`.
    * It's mainly syntax sugar, a convenience for developer experience.

z Scalar) bool { // Compute t1 = (x+y)*z var t1 Scalar t1.Add(&x, &y) t1.Multiply(&t1, &z) // Compute t2 = x*z + y*z var t2 Scalar var t3 Scalar t2.Multiply(&x, &z) t3.Multiply(&y, &z) t2.Add(&t2, &t3) reprT1, reprT2 := t1.Bytes(), t2.Bytes() return t1 == t2 && isReduced(reprT1) && isReduced(reprT2) } if err := quick.Check(multiplyDistributesO, quickCheckConfig(1024)); err != nil { t.Error(err) } } func TestScalarAddLikeSub(t *testing.T) { addLikeSubNeg := func(x, y Scalar) bool { // Compute t1 =...

z Scalar) bool { // Compute t1 = (x+y)*z var t1 Scalar t1.Add(&x, &y) t1.Multiply(&t1, &z) // Compute t2 = x*z + y*z var t2 Scalar var t3 Scalar t2.Multiply(&x, &z) t3.Multiply(&y, &z) t2.Add(&t2, &t3) reprT1, reprT2 := t1.Bytes(), t2.Bytes() return t1 == t2 && isReduced(reprT1) && isReduced(reprT2) } if err := quick.Check(multiplyDistributesO, quickCheckConfig(1024)); err != nil { t.Error(err) } } func TestScalarAddLikeSub(t *testing.T) { addLikeSubNeg := func(x, y Scalar) bool { // Compute t1 =...

        variable TF_USE_LEGACY_KERAS=1 directly or in your python program by
        import os;os.environ["TF_USE_LEGACY_KERAS"]=1. Please note that this
        will set it for all packages in your Python runtime program

*   1.  Change import of keras from tensorflow as follows
*   import tensorflow.keras as keras and import keras to import tf_keras as
    keras
* **Apple Silicon users:** If you previously installed TensorFlow using