"ctx": {
                        "msg": "Expecting property name enclosed in double quotes",
                        "doc": "{some broken json}",
                        "pos": 1,
                        "lineno": 1,
                        "colno": 2,
                    },
                }
            ]
        }
    )


@needs_py310
def test_post_form_for_json(client: TestClient):

	// In both cases the algorithm is a linear scan over the two
	// lists - T's methods and V's methods - simultaneously.
	// Since method tables are stored in a unique sorted order
	// (alphabetical, with no duplicate method names), the scan
	// through V's methods must hit a match for each of T's
	// methods along the way, or else V does not implement T.
	// This lets us run the scan in overall linear time instead of

				if r == r1 {
					return 0
				}
			}
		}
		return noMatch

	case 2:
		if r >= rune[0] && r <= rune[1] {
			return 0
		}
		return noMatch

	case 4, 6, 8:
		// Linear search for a few pairs.
		// Should handle ASCII well.
		for j := 0; j < len(rune); j += 2 {
			if r < rune[j] {
				return noMatch
			}
			if r <= rune[j+1] {
				return j / 2
			}
		}

func TestPrint(t *testing.T) {
	if testing.Short() {
		t.Skip("skipping test in short mode")
	}

	ast, _ := ParseFile(*src_, func(err error) { t.Error(err) }, nil, 0)

	if ast != nil {
		Fprint(testOut(), ast, LineForm)
		fmt.Println()
	}
}

type shortBuffer struct {
	buf []byte
}

func (w *shortBuffer) Write(data []byte) (n int, err error) {
	w.buf = append(w.buf, data...)
	n = len(data)
	if len(w.buf) > 10 {

> li .fa,\n.fc-color-picker > li .fas,\n.fc-color-picker > li .far,\n.fc-color-picker > li .fab,\n.fc-color-picker > li .glyphicon,\n.fc-color-picker > li .ion {\n  transition: -webkit-transform linear .3s;\n  transition: transform linear .3s;\n  transition: transform linear .3s, -webkit-transform linear .3s;\n}\n\n.fc-color-picker > li .fa:hover,\n.fc-color-picker > li .fas:hover,\n.fc-color-picker > li .far:hover,\n.fc-color-picker > li .fab:hover,\n.fc-color-picker > li .glyphicon:hover,\n.fc-color-picker...

  //
  // Proof: For unary einsum equations involving only transpose ("ij->ji") and
  //   traces ("ii->i"), the linear mapping's Jacobian at input x is given
  //   by the function itself. We can verify that the linear map given by the
  //   VJP are einsums with the equations "ji->ij" and "i->ii" respectively,
  //   where the latter represents 'un-tracing', or filling the diagonal with

    }
  }

  private static boolean equal(@Nullable Object a, @Nullable Object b) {
    return a == b || (a != null && a.equals(b));
  }

  // This one-liner saves us from some ugly casts
  protected Entry<K, V> entry(K key, V value) {
    return Helpers.mapEntry(key, value);
  }

  @Override
  protected void expectContents(Collection<Entry<K, V>> expected) {

    }
  }

  private static boolean equal(@Nullable Object a, @Nullable Object b) {
    return a == b || (a != null && a.equals(b));
  }

  // This one-liner saves us from some ugly casts
  protected Entry<K, V> entry(K key, V value) {
    return Helpers.mapEntry(key, value);
  }

  @Override
  protected void expectContents(Collection<Entry<K, V>> expected) {

// CHECK-LABEL: testResourceApplyFtrl
func.func @testResourceApplyFtrl(%var: tensor<*x!tf_type.resource>, %accum: tensor<*x!tf_type.resource>, %linear: tensor<*x!tf_type.resource>, %grad: tensor<*xf32>, %lr: tensor<*xf32>, %l1: tensor<*xf32>, %l2: tensor<*xf32>, %lr_power: tensor<*xf32>) -> () {

		}
		flat, cum := n.FlatValue(), n.CumValue()
		l := &profile.Location{
			ID:      uint64(i + 1),
			Address: n.Info.Address,
			Line: []profile.Line{
				{
					Line:     int64(n.Info.Lineno),
					Column:   int64(n.Info.Columnno),
					Function: f,
				},
			},
		}

		fv, _ := measurement.Scale(flat, o.SampleUnit, o.OutputUnit)
		cv, _ := measurement.Scale(cum, o.SampleUnit, o.OutputUnit)