nvidia-cuda-nvrtc-cu12>=12.5.82,<13.0
nvidia-cuda-runtime-cu12>=12.5.82,<13.0
# The upper bound is set for the CUDNN API compatibility.
# See
# https://docs.nvidia.com/deeplearning/cudnn/backend/latest/developer/forward-compatibility.html#cudnn-api-compatibility
nvidia-cudnn-cu12>=9.3.0.75,<10.0
nvidia-cufft-cu12>=11.2.3.61,<12.0
nvidia-curand-cu12>=10.3.6.82,<11.0
nvidia-cusolver-cu12>=11.6.3.83,<12.0
nvidia-cusparse-cu12>=12.5.1.3,<13.0

# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current
# major release. Example: sm_80 kernels can run on sm_89 GPUs but
# not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.

# Release 2.18.0

## TensorFlow

### Breaking Changes

* `tf.lite`
    * C API:

			sw, tryStringWriter = b.wr.(io.StringWriter)
		}
		if b.Buffered() == 0 && tryStringWriter {
			// Large write, empty buffer, and the underlying writer supports
			// WriteString: forward the write to the underlying StringWriter.
			// This avoids an extra copy.
			n, b.err = sw.WriteString(s)
		} else {
			n = copy(b.buf[b.n:], s)
			b.n += n
			b.Flush()
		}
		nn += n
		s = s[n:]