- Sort Score
- Num 10 results
- Language All
Results 1 - 3 of 3 for 0123 (0.03 seconds)
The search processing time has exceeded the limit. The displayed results may be partial.
-
docs/en/docs/release-notes.md
* ⬆ Bump typer from 0.12.5 to 0.15.3. PR [#13666](https://github.com/fastapi/fastapi/pull/13666) by [@dependabot[bot]](https://github.com/apps/dependabot). * ⬆ Bump sqlmodel from 0.0.23 to 0.0.24. PR [#13665](https://github.com/fastapi/fastapi/pull/13665) by [@dependabot[bot]](https://github.com/apps/dependabot).
Created: Sun Apr 05 07:19:11 GMT 2026 - Last Modified: Fri Apr 03 12:07:04 GMT 2026 - 631K bytes - Click Count (0) -
src/cmd/asm/internal/asm/testdata/amd64enc.s
ADDL $7, (R11) // 41830307 ADDL $7, DX // 83c207 ADDL $7, R11 // 4183c307 ADDL DX, (BX) // 0113 ADDL R11, (BX) // 44011b ADDL DX, (R11) // 410113 ADDL R11, (R11) // 45011b ADDL DX, DX // 01d2 or 03d2
Created: Tue Apr 07 11:13:11 GMT 2026 - Last Modified: Fri Oct 08 21:38:44 GMT 2021 - 581.9K bytes - Click Count (1) -
RELEASE.md
mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True) return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var + 1e-10))` Alternatively, you can override `convolution_op`: `python class StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs, kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2], keepdims=True) # Author code uses std + 1e-5 return
Created: Tue Apr 07 12:39:13 GMT 2026 - Last Modified: Mon Mar 30 18:31:38 GMT 2026 - 746.5K bytes - Click Count (3)