Changed RNN's compute type to fp32. This is because * TF uses fp16 as compute type. * before 7.5.0, compute type fp16 is not implemented. 7.5.0 documents its implementation in the release notes. * we believe that for <7.5.0, fp16 is implemented in terms of fp32. * now we upgrade to 7.5.0, the actual fp16 kicks in and hurts the precision, causing test failures.
Changed RNN's compute type to fp32. This is because
* TF uses fp16 as compute type.
* before 7.5.0, compute type fp16 is not implemented. 7.5.0 documents its implementation in the release notes.
* we believe that for <7.5.0, fp16 is implemented in terms of fp32.
* now we upgrade to 7.5.0, the actual fp16 kicks in and hurts the precision, causing test failures.

Besides, the comment around the fp16 <-> fp32 switch shows that we intended to use fp32 anyway, fp16 is just a workaround. I verified that the fp16 workaround is not needed anymore.

I also ran the RNN benchmark //third_party/tensorflow/contrib/cudnn_rnn:cudnn_rnn_ops_benchmark and didn't find any performance regression.

fp16 + 7.4.2
cudnn_lstm small y4_u128_b64_q50 takes 0.0121 sec/step
cudnn_lstm medium y4_u512_b64_q50 takes 0.0197 sec/step
cudnn_lstm large y4_u1024_b64_q50 takes 0.0640 sec/step
tf_rnn_lstm_block_cell small y4_u128_b64_q50 takes 0.0463 sec/step
tf_rnn_lstm_block_cell medium y4_u512_b64_q50 takes 0.0603 sec/step
tf_rnn_lstm_block_cell large y4_u1024_b64_q50 takes 0.1257 sec/step
tf_rnn_lstm small y4_u128_b64_q50 takes 0.0552 sec/step
tf_rnn_lstm medium y4_u512_b64_q50 takes 0.0708 sec/step
tf_rnn_lstm large y4_u1024_b64_q50 takes 0.1376 sec/step
fp32 + 7.4.2
cudnn_lstm small y4_u128_b64_q50 takes 0.0105 sec/step
cudnn_lstm medium y4_u512_b64_q50 takes 0.0192 sec/step
cudnn_lstm large y4_u1024_b64_q50 takes 0.0639 sec/step
tf_rnn_lstm_block_cell small y4_u128_b64_q50 takes 0.0465 sec/step
tf_rnn_lstm_block_cell medium y4_u512_b64_q50 takes 0.0629 sec/step
tf_rnn_lstm_block_cell large y4_u1024_b64_q50 takes 0.1271 sec/step
tf_rnn_lstm small y4_u128_b64_q50 takes 0.0575 sec/step
tf_rnn_lstm medium y4_u512_b64_q50 takes 0.0701 sec/step
tf_rnn_lstm large y4_u1024_b64_q50 takes 0.1356 sec/step
fp16 + 7.5.0
cudnn_lstm small y4_u128_b64_q50 takes 0.0110 sec/step
cudnn_lstm medium y4_u512_b64_q50 takes 0.0190 sec/step
cudnn_lstm large y4_u1024_b64_q50 takes 0.0636 sec/step
tf_rnn_lstm_block_cell small y4_u128_b64_q50 takes 0.0495 sec/step
tf_rnn_lstm_block_cell medium y4_u512_b64_q50 takes 0.0611 sec/step
tf_rnn_lstm_block_cell large y4_u1024_b64_q50 takes 0.1264 sec/step
tf_rnn_lstm small y4_u128_b64_q50 takes 0.0588 sec/step
tf_rnn_lstm medium y4_u512_b64_q50 takes 0.0697 sec/step
tf_rnn_lstm large y4_u1024_b64_q50 takes 0.1365 sec/step
fp32 + 7.5.0
cudnn_lstm small y4_u128_b64_q50 takes 0.0106 sec/step
cudnn_lstm medium y4_u512_b64_q50 takes 0.0192 sec/step
cudnn_lstm large y4_u1024_b64_q50 takes 0.0638 sec/step
tf_rnn_lstm_block_cell small y4_u128_b64_q50 takes 0.0474 sec/step
tf_rnn_lstm_block_cell medium y4_u512_b64_q50 takes 0.0615 sec/step
tf_rnn_lstm_block_cell large y4_u1024_b64_q50 takes 0.1273 sec/step
tf_rnn_lstm small y4_u128_b64_q50 takes 0.0592 sec/step
tf_rnn_lstm medium y4_u512_b64_q50 takes 0.0702 sec/step
tf_rnn_lstm large y4_u1024_b64_q50 takes 0.1360 sec/step

PiperOrigin-RevId: 245104419

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