Add generic fake quantized embedding for QAT

[andrewor14]

Summary: This is equivalent to #1020 but for nn.Embedding. This commit adds a generic fake quantized embedding module to replace the uses of the existing more specific QAT embeddings. For example, Int4WeightOnlyQATEmbedding can be expressed as follows:

from torchao.quantization.prototype.qat.api import FakeQuantizeConfig
from torchao.quantization.prototype.qat.embedding import FakeQuantizedEmbedding

weight_config = FakeQuantizeConfig(
    dtype=torch.int4,
    group_size=group_size,
    is_symmetric=True,
)
fq_embedding = FakeQuantizedEmbedding(16, 32, weight_config=weight_config)

Test Plan:
python test/quantization/test_qat.py -k test_qat_4w_embedding
python test/quantization/test_qat.py -k test_fake_quantized_embedding_4w

[pytorch-bot]

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