Clippy fixes.

examples/min-gpt/main.rs

@@ -80,7 +80,7 @@ fn causal_self_attention(p: &nn::Path, cfg: Config) -> impl ModuleT {
         let q = xs.apply(&query).view(sizes).transpose(1, 2);
         let v = xs.apply(&value).view(sizes).transpose(1, 2);
         let att = q.matmul(&k.transpose(-2, -1)) * (1.0 / f64::sqrt(sizes[3] as f64));
-        let att = att.masked_fill(&mask.i((.., .., ..sz_t, ..sz_t)).eq(0.), std::f64::NEG_INFINITY);
+        let att = att.masked_fill(&mask.i((.., .., ..sz_t, ..sz_t)).eq(0.), f64::NEG_INFINITY);
         let att = att.softmax(-1, Kind::Float).dropout(cfg.attn_pdrop, train);
         let ys = att.matmul(&v).transpose(1, 2).contiguous().view([sz_b, sz_t, sz_c]);
         ys.apply(&proj).dropout(cfg.resid_pdrop, train)

src/nn/init.rs

@@ -107,7 +107,7 @@ pub fn f_init(i: Init, dims: &[i64], device: Device) -> Result<Tensor, TchError>
             // Optimize the case for which a single C++ code can be done.
             if cst == 0. {
                 Tensor::f_zeros(dims, (Kind::Float, device))
-            } else if (cst - 1.).abs() <= std::f64::EPSILON {
+            } else if (cst - 1.).abs() <= f64::EPSILON {
                 Tensor::f_ones(dims, (Kind::Float, device))
             } else {
                 Tensor::f_ones(dims, (Kind::Float, device)).map(|t| t * cst)
@@ -117,7 +117,7 @@ pub fn f_init(i: Init, dims: &[i64], device: Device) -> Result<Tensor, TchError>
             Tensor::f_zeros(dims, (Kind::Float, device))?.f_uniform_(lo, up)
         }
         Init::Randn { mean, stdev } => {
-            if mean == 0. && (stdev - 1.).abs() <= std::f64::EPSILON {
+            if mean == 0. && (stdev - 1.).abs() <= f64::EPSILON {
                 Tensor::f_randn(dims, (Kind::Float, device))
             } else {
                 Tensor::f_randn(dims, (Kind::Float, device)).map(|t| t * stdev + mean)